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\n \n\n \n \n \n \n \n \n Prognostic impact of germline deleterious variants and variants of uncertain significance in advanced prostate cancer: A call for functional elucidation.\n \n \n \n \n\n\n \n Alonso Monasterio, M.; Tellaetxe Elorriaga, I.; Fernández, R.; Carrera, S.; Jiménez Labaig, P.; Mosteiro, L.; Vázquez, M.; García-Olaverri, J.; Iturregui, A. M.; Büchser, D.; Gómez-Iturriaga, A.; Urresola, A.; Fernández, I.; Iza, E.; Iruarrizaga, E.; Mañe, J. M.; Elcoroaristizabal, X.; Ruiz-Ontañón, P.; Erramuzpe, A.; and Novo, E.\n\n\n \n\n\n\n Journal of Clinical Oncology, 43(5_suppl): 211–211. February 2025.\n \n\n\n\n
\n\n\n\n \n \n $\"Prognostic$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{alonso_monasterio_prognostic_2025,\n\ttitle = {Prognostic impact of germline deleterious variants and variants of uncertain significance in advanced prostate cancer: {A} call for functional elucidation.},\n\tvolume = {43},\n\tissn = {0732-183X, 1527-7755},\n\tshorttitle = {Prognostic impact of germline deleterious variants and variants of uncertain significance in advanced prostate cancer},\n\turl = {https://ascopubs.org/doi/10.1200/JCO.2025.43.5_suppl.211},\n\tdoi = {10.1200/JCO.2025.43.5_suppl.211},\n\tabstract = {211\n            \n            \n              Background:\n              Prostate cancer remains the most prevalent solid tumor in men and the third leading cause of cancer-related mortality globally. Tumor aggressiveness and poorer clinical outcomes are associated with certain germline variants. Current technological developments in genetic testing have improved the identification of variants of uncertain significance (VUS), adding complexity to the challenging process of clinical decision-making. The aim of this project was to explore the potential correlation between the identified germline variants and the clinical outcomes in patients with metastatic prostate cancer (mPC).\n              Methods:\n              This retrospective study was conducted at a tertiary care center and included a cohort of 57 patients with mPC who underwent germline genetic testing from January 2021 to December 2022. DNA sequencing was performed by next-generation sequencing (Miniseq, Illumina) using a custom gene panel of 72 genes, and two commercial software packages were employed for variant identification. Variant reanalysis was performed in April 2024. A descriptive and exploratory statistical analysis together with a survival analysis was conducted. Hazard ratios (HRs) with 95\\% confidence intervals (CIs) estimated with the Cox Proportional Hazards model and p-values for the survival curves obtained by the Kaplan-Meier estimator are presented.\n              Results:\n              A total of 57 patients were included in the analysis, of whom 27/57 (47.5\\%) had synchronous metastatic disease, while 18/57 (39.1\\%) had a high-volume tumor (CHAARTED criteria) and 22/57 (47.8\\%) had high-risk disease (LATITUDE criteria). Of all patients, 19 (33,3\\%) carried reportable germline variants. Of these, 5 (15.8\\%) were classified as pathogenic or likely pathogenic, 14 (73.68\\%) were classified as VUS and in two cases (10.53\\%) both co-occurred. The impact of the reported variants (including VUS) in homologous recombination repair (HRR) genes (\n              BRCA1, BRCA2, BARD1, RAD50, RAD51C, RAD51D, PALB2, ATM, CHEK2, NBN\n              ) is summarized in the accompanying table.\n              Conclusions:\n              These results seem to indicate that carrying a VUS in an HRR gene could be associated with worse overall survival. This finding further emphasizes the need to report and elucidate the clinical significance of VUS through precise functional studies. A comprehensive somatic and clinical outcome analysis is ongoing.\n              \n                \n                  Survival analysis summary.\n                \n                \n                  \n                    \n                      Germline HRRreportable variants\n                      mOS* (months)\n                      mOS* (months)\n                      N(patients with reportable variants)\n                      HR 95\\% CI\n                      p- value\n                    \n                  \n                  \n                    \n                      Pathogenic/Likely Pathogenic vs. None (including VUS)\n                      53.4\n                      56.3\n                      3\n                      1.27[0.38 – 4.20]\n                      0.86\n                    \n                    \n                      Only VUS vs. None\n                      40.4\n                      72.0\n                      11**\n                      1.76[0.73 – 4.21]\n                      0.0478\n                    \n                    \n                      All vs. None\n                      50.3\n                      72.0\n                      14\n                      2.05[0.99 – 4.24]\n                      0.0263\n                    \n                  \n                \n                \n                  \n                    *The diagnosis of metastatic prostate cancer serves as the baseline for OS.\n                  \n                  \n                    **One patient was excluded from analysis for having both pathogenic and VUS HRR variants.},\n\tlanguage = {en},\n\tnumber = {5\\_suppl},\n\turldate = {2025-02-24},\n\tjournal = {Journal of Clinical Oncology},\n\tauthor = {Alonso Monasterio, Maitane and Tellaetxe Elorriaga, Iñigo and Fernández, Ricardo and Carrera, Sergio and Jiménez Labaig, Pablo and Mosteiro, Lorena and Vázquez, Manuela and García-Olaverri, Jorge and Iturregui, Ane Miren and Büchser, David and Gómez-Iturriaga, Alfonso and Urresola, Aranzazu and Fernández, Iratxe and Iza, Estibaliz and Iruarrizaga, Eluska and Mañe, Joan Manel and Elcoroaristizabal, Xabier and Ruiz-Ontañón, Patricia and Erramuzpe, Asier and Novo, Eneko},\n\tmonth = feb,\n\tyear = {2025},\n\tpages = {211--211},\n}\n\n\n\n

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\n 211 Background: Prostate cancer remains the most prevalent solid tumor in men and the third leading cause of cancer-related mortality globally. Tumor aggressiveness and poorer clinical outcomes are associated with certain germline variants. Current technological developments in genetic testing have improved the identification of variants of uncertain significance (VUS), adding complexity to the challenging process of clinical decision-making. The aim of this project was to explore the potential correlation between the identified germline variants and the clinical outcomes in patients with metastatic prostate cancer (mPC). Methods: This retrospective study was conducted at a tertiary care center and included a cohort of 57 patients with mPC who underwent germline genetic testing from January 2021 to December 2022. DNA sequencing was performed by next-generation sequencing (Miniseq, Illumina) using a custom gene panel of 72 genes, and two commercial software packages were employed for variant identification. Variant reanalysis was performed in April 2024. A descriptive and exploratory statistical analysis together with a survival analysis was conducted. Hazard ratios (HRs) with 95% confidence intervals (CIs) estimated with the Cox Proportional Hazards model and p-values for the survival curves obtained by the Kaplan-Meier estimator are presented. Results: A total of 57 patients were included in the analysis, of whom 27/57 (47.5%) had synchronous metastatic disease, while 18/57 (39.1%) had a high-volume tumor (CHAARTED criteria) and 22/57 (47.8%) had high-risk disease (LATITUDE criteria). Of all patients, 19 (33,3%) carried reportable germline variants. Of these, 5 (15.8%) were classified as pathogenic or likely pathogenic, 14 (73.68%) were classified as VUS and in two cases (10.53%) both co-occurred. The impact of the reported variants (including VUS) in homologous recombination repair (HRR) genes ( BRCA1, BRCA2, BARD1, RAD50, RAD51C, RAD51D, PALB2, ATM, CHEK2, NBN ) is summarized in the accompanying table. Conclusions: These results seem to indicate that carrying a VUS in an HRR gene could be associated with worse overall survival. This finding further emphasizes the need to report and elucidate the clinical significance of VUS through precise functional studies. A comprehensive somatic and clinical outcome analysis is ongoing. Survival analysis summary. Germline HRRreportable variants mOS* (months) mOS* (months) N(patients with reportable variants) HR 95% CI p- value Pathogenic/Likely Pathogenic vs. None (including VUS) 53.4 56.3 3 1.27[0.38 – 4.20] 0.86 Only VUS vs. None 40.4 72.0 11** 1.76[0.73 – 4.21] 0.0478 All vs. None 50.3 72.0 14 2.05[0.99 – 4.24] 0.0263 *The diagnosis of metastatic prostate cancer serves as the baseline for OS. **One patient was excluded from analysis for having both pathogenic and VUS HRR variants.\n

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\n \n\n \n \n \n \n \n \n AgeML: Age modeling with Machine Learning.\n \n \n \n \n\n\n \n Condado, J. G.; Elorriaga, I. T.; Cortes, J. M.; and Erramuzpe, A.\n\n\n \n\n\n\n IEEE Journal of Biomedical and Health Informatics,1–11. 2025.\n \n\n\n\n
\n\n\n\n \n \n $\"AgeML:$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{condado_ageml_2025,\n\ttitle = {{AgeML}: {Age} modeling with {Machine} {Learning}},\n\tcopyright = {https://creativecommons.org/licenses/by/4.0/legalcode},\n\tissn = {2168-2194, 2168-2208},\n\tshorttitle = {{AgeML}},\n\turl = {https://ieeexplore.ieee.org/document/10844538/},\n\tdoi = {10.1109/JBHI.2025.3531017},\n\turldate = {2025-01-29},\n\tjournal = {IEEE Journal of Biomedical and Health Informatics},\n\tauthor = {Condado, Jorge Garcia and Elorriaga, Iñigo Tellaetxe and Cortes, Jesus M. and Erramuzpe, Asier},\n\tyear = {2025},\n\tpages = {1--11},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Systemic cellular migration: The forces driving the directed locomotion movement of cells.\n \n \n \n \n\n\n \n De La Fuente, I. M; Carrasco-Pujante, J.; Camino-Pontes, B.; Fedetz, M.; Bringas, C.; Pérez-Samartín, A.; Pérez-Yarza, G.; López, J. I; Malaina, I.; and Cortes, J. M\n\n\n \n\n\n\n PNAS Nexus, 3(5): pgae171. April 2024.\n \n\n\n\n
\n\n\n\n \n \n $\"Systemic$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n \n \n 2 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{de_la_fuente_systemic_2024,\n\ttitle = {Systemic cellular migration: {The} forces driving the directed locomotion movement of cells},\n\tvolume = {3},\n\tcopyright = {https://creativecommons.org/licenses/by/4.0/},\n\tissn = {2752-6542},\n\tshorttitle = {Systemic cellular migration},\n\turl = {https://academic.oup.com/pnasnexus/article/doi/10.1093/pnasnexus/pgae171/7655426},\n\tdoi = {10.1093/pnasnexus/pgae171},\n\tabstract = {Abstract \n            Directional motility is an essential property of cells. Despite its enormous relevance in many fundamental physiological and pathological processes, how cells control their locomotion movements remains an unresolved question. Here, we have addressed the systemic processes driving the directed locomotion of cells. Specifically, we have performed an exhaustive study analyzing the trajectories of 700 individual cells belonging to three different species (Amoeba proteus, Metamoeba leningradensis, and Amoeba borokensis) in four different scenarios: in absence of stimuli, under an electric field (galvanotaxis), in a chemotactic gradient (chemotaxis), and under simultaneous galvanotactic and chemotactic stimuli. All movements were analyzed using advanced quantitative tools. The results show that the trajectories are mainly characterized by coherent integrative responses that operate at the global cellular scale. These systemic migratory movements depend on the cooperative nonlinear interaction of most, if not all, molecular components of cells.},\n\tlanguage = {en},\n\tnumber = {5},\n\turldate = {2024-11-16},\n\tjournal = {PNAS Nexus},\n\tauthor = {De La Fuente, Ildefonso M and Carrasco-Pujante, Jose and Camino-Pontes, Borja and Fedetz, Maria and Bringas, Carlos and Pérez-Samartín, Alberto and Pérez-Yarza, Gorka and López, José I and Malaina, Iker and Cortes, Jesus M},\n\teditor = {Espinosa, Horacio},\n\tmonth = apr,\n\tyear = {2024},\n\tpages = {pgae171},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Disentangling high-order effects in the transfer entropy.\n \n \n \n \n\n\n \n Stramaglia, S.; Faes, L.; Cortes, J. M.; and Marinazzo, D.\n\n\n \n\n\n\n Physical Review Research, 6(3): L032007. July 2024.\n \n\n\n\n
\n\n\n\n \n \n $\"Disentangling$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n \n \n 1 download\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{stramaglia_disentangling_2024,\n\ttitle = {Disentangling high-order effects in the transfer entropy},\n\tvolume = {6},\n\tissn = {2643-1564},\n\turl = {https://link.aps.org/doi/10.1103/PhysRevResearch.6.L032007},\n\tdoi = {10.1103/PhysRevResearch.6.L032007},\n\tabstract = {Transfer entropy (TE), the primary method for determining directed information flow within a network system, can exhibit bias—either in deficiency or excess—during both pairwise and conditioned calculations, owing to high-order dependencies among the dynamic processes under consideration and the remaining processes in the system used for conditioning. Here, we propose a novel approach. Instead of conditioning TE on all network processes except the driver and the target, as in its fully conditioned version, or not conditioning at all, as in the pairwise approach, our method searches for both the multiplets of variables that maximize information flow and those that minimize it. This provides a decomposition of TE into unique, redundant, and synergistic atoms. Our approach enables the quantification of the relative importance of high-order effects compared to pure two-body effects in information transfer between two processes, while also highlighting the processes that contribute to building these high-order effects alongside the driver. We demonstrate the application of our approach in climatology by analyzing data from El Niño and the Southern Oscillation. \n             \n               \n               \n                 \n                  Published by the American Physical Society \n                  2024},\n\tlanguage = {en},\n\tnumber = {3},\n\turldate = {2024-11-16},\n\tjournal = {Physical Review Research},\n\tauthor = {Stramaglia, Sebastiano and Faes, Luca and Cortes, Jesus M. and Marinazzo, Daniele},\n\tmonth = jul,\n\tyear = {2024},\n\tpages = {L032007},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Reorganization of integration and segregation networks in brain-based visual impairment.\n \n \n \n \n\n\n \n Diez, I.; Troyas, C.; Bauer, C. M.; Sepulcre, J.; and Merabet, L. B.\n\n\n \n\n\n\n NeuroImage: Clinical, 44: 103688. January 2024.\n \n\n\n\n
\n\n\n\n \n \n $\"Reorganization$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

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@article{diez_reorganization_2024,\n\ttitle = {Reorganization of integration and segregation networks in brain-based visual impairment},\n\tvolume = {44},\n\tissn = {2213-1582},\n\turl = {https://www.sciencedirect.com/science/article/pii/S2213158224001293},\n\tdoi = {10.1016/j.nicl.2024.103688},\n\tabstract = {Growing evidence suggests that cerebral connectivity changes its network organization by altering modular topology in response to developmental and environmental experience. However, changes in cerebral connectivity associated with visual impairment due to early neurological injury are still not fully understood. Cerebral visual impairment (CVI) is a brain-based visual disorder associated with damage and maldevelopment of retrochiasmal pathways and areas implicated in visual processing. In this study, we used a multimodal imaging approach and connectomic analyses based on structural (voxel-based morphometry; VBM) and resting state functional connectivity (rsfc) to investigate differences in weighted degree and link-level connectivity in individuals with CVI compared to controls with neurotypical development. We found that participants with CVI showed significantly reduced grey matter volume within the primary visual cortex and intraparietal sulcus (IPS) compared to controls. Participants with CVI also exhibited marked reorganization characterized by increased integration of visual connectivity to somatosensory and multimodal integration areas (dorsal and ventral attention regions) and lower connectivity from visual to limbic and default mode networks. Link-level functional changes in CVI were also associated with key clinical outcomes related to visual function and development. These findings provide early insight into how visual impairment related to early brain injury distinctly reorganizes the functional network architecture of the human brain.},\n\turldate = {2024-11-16},\n\tjournal = {NeuroImage: Clinical},\n\tauthor = {Diez, Ibai and Troyas, Carla and Bauer, Corinna M. and Sepulcre, Jorge and Merabet, Lotfi B.},\n\tmonth = jan,\n\tyear = {2024},\n\tkeywords = {Cerebral visual impairment, Connectomics, Link-level, Resting state functional connectivity, Voxel-based morphometry, Weighted degree},\n\tpages = {103688},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Open datasets and code for multi-scale relations on structure, function and neuro-genetics in the human brain.\n \n \n \n \n\n\n \n Jimenez-Marin, A.; Diez, I.; Erramuzpe, A.; Stramaglia, S.; Bonifazi, P.; and Cortes, J. M.\n\n\n \n\n\n\n Scientific Data, 11(1): 256. February 2024.\n \n\n\n\n
\n\n\n\n \n \n $\"Open$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n \n \n 2 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{jimenez-marin_open_2024,\n\ttitle = {Open datasets and code for multi-scale relations on structure, function and neuro-genetics in the human brain},\n\tvolume = {11},\n\tissn = {2052-4463},\n\turl = {https://www.nature.com/articles/s41597-024-03060-2},\n\tdoi = {10.1038/s41597-024-03060-2},\n\tabstract = {Abstract\n            The human brain is an extremely complex network of structural and functional connections that operate at multiple spatial and temporal scales. Investigating the relationship between these multi-scale connections is critical to advancing our comprehension of brain function and disorders. However, accurately predicting structural connectivity from its functional counterpart remains a challenging pursuit. One of the major impediments is the lack of public repositories that integrate structural and functional networks at diverse resolutions, in conjunction with modular transcriptomic profiles, which are essential for comprehensive biological interpretation. To mitigate this limitation, our contribution encompasses the provision of an open-access dataset consisting of derivative matrices of functional and structural connectivity across multiple scales, accompanied by code that facilitates the investigation of their interrelations. We also provide additional resources focused on neuro-genetic associations of module-level network metrics, which present promising opportunities to further advance research in the field of network neuroscience, particularly concerning brain disorders.},\n\tlanguage = {en},\n\tnumber = {1},\n\turldate = {2024-04-15},\n\tjournal = {Scientific Data},\n\tauthor = {Jimenez-Marin, Antonio and Diez, Ibai and Erramuzpe, Asier and Stramaglia, Sebastiano and Bonifazi, Paolo and Cortes, Jesus M.},\n\tmonth = feb,\n\tyear = {2024},\n\tpages = {256},\n}\n\n\n\n\n\n\n\n\n\n\n\n

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\n \n\n \n \n \n \n \n \n Cognitive and brain connectivity trajectories in critically ill COVID-19 patients.\n \n \n \n \n\n\n \n Ramos-Usuga, D.; Jimenez-Marin, A.; Cabrera-Zubizarreta, A.; Benito-Sanchez, I.; Rivera, D.; Martínez-Gutiérrez, E.; Panera, E.; Boado, V.; Labayen, F.; Cortes, J. M.; and Arango-Lasprilla, J. C.\n\n\n \n\n\n\n NeuroRehabilitation,1–13. February 2024.\n \n\n\n\n
\n\n\n\n \n \n $\"Cognitive$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n \n \n 3 downloads\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{ramos-usuga_cognitive_2024,\n\ttitle = {Cognitive and brain connectivity trajectories in critically ill {COVID}-19 patients},\n\tissn = {10538135, 18786448},\n\turl = {https://www.medra.org/servlet/aliasResolver?alias=iospress&doi=10.3233/NRE-230216},\n\tdoi = {10.3233/NRE-230216},\n\tabstract = {BACKGROUND: Multiple Organ failure (MOF) is one of the main causes of admission to the Intensive Care Unit (ICU) of patients infected with COVID-19 and can cause short- and long-term neurological deficits. OBJECTIVE: To compare the cognitive functioning and functional brain connectivity at 6–12 months after discharge in two groups of individuals with MOF, one due to COVID-19 and the other due to another cause (MOF-group), with a group of Healthy Controls (HC). METHODS: Thirty-six participants, 12 from each group, underwent a neuropsychological and neuroimaging assessment at both time-points. Functional connectivity of the resting state networks was compared between COVID-19 and HC while controlling for the effect of MOF. The association between functional connectivity and neuropsychological performance was also investigated. RESULTS: Compared to the HC, COVID-19 group demonstrated hypoconnectivity between the Default Mode Network and Salience Network. This pattern was associated with worse performance on tests of attention and information processing speed, at both time-points. CONCLUSION: The study of the association between cognitive function and brain functional connectivity in COVID-19 allows the understanding of the short- and long-term neurological alterations of this disease and promotes the development of intervention programs to improve the quality of life for this understudied population.},\n\turldate = {2024-04-15},\n\tjournal = {NeuroRehabilitation},\n\tauthor = {Ramos-Usuga, Daniela and Jimenez-Marin, Antonio and Cabrera-Zubizarreta, Alberto and Benito-Sanchez, Itziar and Rivera, Diego and Martínez-Gutiérrez, Endika and Panera, Elena and Boado, Victoria and Labayen, Fermín and Cortes, Jesus M. and Arango-Lasprilla, Juan C.},\n\tmonth = feb,\n\tyear = {2024},\n\tpages = {1--13},\n}\n\n\n\n\n\n\n\n

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\n \n\n \n \n \n \n \n \n Induction of Translational Readthrough on Protein Tyrosine Phosphatases Targeted by Premature Termination Codon Mutations in Human Disease.\n \n \n \n \n\n\n \n Torices, L.; Nunes-Xavier, C. E.; Mingo, J.; Luna, S.; Erramuzpe, A.; Cortés, J. M.; and Pulido, R.\n\n\n \n\n\n\n In Thévenin, D.; and P. Müller, J., editor(s), Protein Tyrosine Phosphatases, volume 2743, pages 1–19. Springer US, New York, NY, 2024.\n Series Title: Methods in Molecular Biology\n\n\n\n
\n\n\n\n \n \n $\"Induction$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@incollection{thevenin_induction_2024,\n\taddress = {New York, NY},\n\ttitle = {Induction of {Translational} {Readthrough} on {Protein} {Tyrosine} {Phosphatases} {Targeted} by {Premature} {Termination} {Codon} {Mutations} in {Human} {Disease}},\n\tvolume = {2743},\n\tisbn = {978-1-07-163568-1 978-1-07-163569-8},\n\turl = {https://link.springer.com/10.1007/978-1-0716-3569-8_1},\n\tlanguage = {en},\n\turldate = {2024-04-15},\n\tbooktitle = {Protein {Tyrosine} {Phosphatases}},\n\tpublisher = {Springer US},\n\tauthor = {Torices, Leire and Nunes-Xavier, Caroline E. and Mingo, Janire and Luna, Sandra and Erramuzpe, Asier and Cortés, Jesús M. and Pulido, Rafael},\n\teditor = {Thévenin, Damien and P. Müller, Jörg},\n\tyear = {2024},\n\tdoi = {10.1007/978-1-0716-3569-8_1},\n\tnote = {Series Title: Methods in Molecular Biology},\n\tpages = {1--19},\n}\n\n\n\n

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\n \n 2023\n \n \n (5)\n \n \n

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\n \n\n \n \n \n \n \n \n One‐year prediction of cognitive decline following cognitive‐stimulation from real‐world data.\n \n \n \n \n\n\n \n Camino‐Pontes, B.; Gonzalez‐Lopez, F.; Santamaría‐Gomez, G.; Sutil‐Jimenez, A. J.; Sastre‐Barrios, C.; De Pierola, I. F.; and Cortes, J. M.\n\n\n \n\n\n\n Journal of Neuropsychology, 17(2): 302–318. June 2023.\n \n\n\n\n
\n\n\n\n \n \n $\"One‐year$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{caminopontes_oneyear_2023,\n\ttitle = {One‐year prediction of cognitive decline following cognitive‐stimulation from real‐world data},\n\tvolume = {17},\n\tissn = {1748-6645, 1748-6653},\n\turl = {https://bpspsychub.onlinelibrary.wiley.com/doi/10.1111/jnp.12307},\n\tdoi = {10.1111/jnp.12307},\n\tabstract = {Abstract\n            Clinical evidence based on real‐world data (RWD) is accumulating exponentially providing larger sample sizes available, which demand novel methods to deal with the enhanced heterogeneity of the data. Here, we used RWD to assess the prediction of cognitive decline in a large heterogeneous sample of participants being enrolled with cognitive stimulation, a phenomenon that is of great interest to clinicians but that is riddled with difficulties and limitations. More precisely, from a multitude of neuropsychological Training Materials (TMs), we asked whether was possible to accurately predict an individual's cognitive decline one year after being tested. In particular, we performed longitudinal modelling of the scores obtained from 215 different tests, grouped into 29 cognitive domains, a total of 124,610 instances from 7902 participants (40\\% male, 46\\% female, 14\\% not indicated), each performing an average of 16 tests. Employing a machine learning approach based on ROC analysis and cross‐validation techniques to overcome overfitting, we show that different TMs belonging to several cognitive domains can accurately predict cognitive decline, while other domains perform poorly, suggesting that the ability to predict decline one year later is not specific to any particular domain, but is rather widely distributed across domains. Moreover, when addressing the same problem between individuals with a common diagnosed label, we found that some domains had more accurate classification for conditions such as Parkinson's disease and Down syndrome, whereas they are less accurate for Alzheimer's disease or multiple sclerosis. Future research should combine similar approaches to ours with standard neuropsychological measurements to enhance interpretability and the possibility of generalizing across different cohorts.},\n\tlanguage = {en},\n\tnumber = {2},\n\turldate = {2024-04-15},\n\tjournal = {Journal of Neuropsychology},\n\tauthor = {Camino‐Pontes, Borja and Gonzalez‐Lopez, Francisco and Santamaría‐Gomez, Gonzalo and Sutil‐Jimenez, Antonio Javier and Sastre‐Barrios, Carolina and De Pierola, Iñigo Fernandez and Cortes, Jesus M.},\n\tmonth = jun,\n\tyear = {2023},\n\tpages = {302--318},\n}\n\n\n\n\n\n\n\n

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\n \n\n \n \n \n \n \n \n NeuropsychBrainAge: A biomarker for conversion from mild cognitive impairment to Alzheimer's disease.\n \n \n \n \n\n\n \n Garcia Condado, J.; Cortes, J. M.; and for the Alzheimer's Disease Neuroimaging Initiative\n\n\n \n\n\n\n Alzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring, 15(4): e12493. October 2023.\n \n\n\n\n
\n\n\n\n \n \n $\"NeuropsychBrainAge:$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{garcia_condado_neuropsychbrainage_2023,\n\ttitle = {{NeuropsychBrainAge}: {A} biomarker for conversion from mild cognitive impairment to {Alzheimer}'s disease},\n\tvolume = {15},\n\tissn = {2352-8729, 2352-8729},\n\tshorttitle = {{NeuropsychBrainAge}},\n\turl = {https://alz-journals.onlinelibrary.wiley.com/doi/10.1002/dad2.12493},\n\tdoi = {10.1002/dad2.12493},\n\tabstract = {Abstract\n            \n              INTRODUCTION\n              BrainAge models based on neuroimaging data have diagnostic classification power but have replicability issues due to site and patient variability. BrainAge models trained on neuropsychological tests could help distinguish stable mild cognitive impairment (sMCI) from progressive MCI (pMCI) to Alzheimer's disease (AD).\n            \n            \n              METHODS\n              A linear regressor BrainAge model was trained on healthy controls using neuropsychological tests and neuroimaging features separately. The BrainAge delta, predicted age minus chronological age, was used to distinguish between sMCI and pMCI.\n            \n            \n              RESULTS\n              The cross‐validated area under the receiver‐operating characteristic (ROC) curve for sMCI versus pMCI was 0.91 for neuropsychological features in contrast to 0.68 for neuroimaging features. The BrainAge delta was correlated with the time to conversion, the time taken for a pMCI subject to convert to AD.\n            \n            \n              DISCUSSION\n              The BrainAge delta from neuropsychological tests is a good biomarker to distinguish between sMCI and pMCI. Other neurological and psychiatric disorders could be studied using this strategy.\n            \n            \n              Highlights\n              \n                \n                  \n                    BrainAge models based on neuropsychological tests outperform models based on neuroimaging features when distinguishing between stable mild cognitive impairment (sMCI) from progressive MCI (pMCI) to Alzheimer's disease (AD).\n                  \n                  \n                    The combination of neuropsychological tests with neuroimaging features does not lead to an improvement in sMCI versus pMCI classification compared to using neuropsychological tests on their own.\n                  \n                  \n                    BrainAge delta of both neuroimaging and neuropsychological models was correlated with the time to conversion, the time taken for a pMCI subject to convert to AD.},\n\tlanguage = {en},\n\tnumber = {4},\n\turldate = {2024-04-15},\n\tjournal = {Alzheimer's \\& Dementia: Diagnosis, Assessment \\& Disease Monitoring},\n\tauthor = {Garcia Condado, Jorge and Cortes, Jesus M. and {for the Alzheimer's Disease Neuroimaging Initiative}},\n\tmonth = oct,\n\tyear = {2023},\n\tpages = {e12493},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Melanoma Clinical Decision Support System: An Artificial Intelligence-Based Tool to Diagnose and Predict Disease Outcome in Early-Stage Melanoma Patients.\n \n \n \n \n\n\n \n Diaz-Ramón, J. L.; Gardeazabal, J.; Izu, R. M.; Garrote, E.; Rasero, J.; Apraiz, A.; Penas, C.; Seijo, S.; Lopez-Saratxaga, C.; De La Peña, P. M.; Sanchez-Diaz, A.; Cancho-Galan, G.; Velasco, V.; Sevilla, A.; Fernandez, D.; Cuenca, I.; Cortes, J. M.; Alonso, S.; Asumendi, A.; and Boyano, M. D.\n\n\n \n\n\n\n Cancers, 15(7): 2174. April 2023.\n \n\n\n\n
\n\n\n\n \n \n $\"Melanoma$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{diaz-ramon_melanoma_2023,\n\ttitle = {Melanoma {Clinical} {Decision} {Support} {System}: {An} {Artificial} {Intelligence}-{Based} {Tool} to {Diagnose} and {Predict} {Disease} {Outcome} in {Early}-{Stage} {Melanoma} {Patients}},\n\tvolume = {15},\n\tcopyright = {https://creativecommons.org/licenses/by/4.0/},\n\tissn = {2072-6694},\n\tshorttitle = {Melanoma {Clinical} {Decision} {Support} {System}},\n\turl = {https://www.mdpi.com/2072-6694/15/7/2174},\n\tdoi = {10.3390/cancers15072174},\n\tabstract = {This study set out to assess the performance of an artificial intelligence (AI) algorithm based on clinical data and dermatoscopic imaging for the early diagnosis of melanoma, and its capacity to define the metastatic progression of melanoma through serological and histopathological biomarkers, enabling dermatologists to make more informed decisions about patient management. Integrated analysis of demographic data, images of the skin lesions, and serum and histopathological markers were analyzed in a group of 196 patients with melanoma. The interleukins (ILs) IL-4, IL-6, IL-10, and IL-17A as well as IFNγ (interferon), GM-CSF (granulocyte and macrophage colony-stimulating factor), TGFβ (transforming growth factor), and the protein DCD (dermcidin) were quantified in the serum of melanoma patients at the time of diagnosis, and the expression of the RKIP, PIRIN, BCL2, BCL3, MITF, and ANXA5 proteins was detected by immunohistochemistry (IHC) in melanoma biopsies. An AI algorithm was used to improve the early diagnosis of melanoma and to predict the risk of metastasis and of disease-free survival. Two models were obtained to predict metastasis (including “all patients” or only patients “at early stages of melanoma”), and a series of attributes were seen to predict the progression of metastasis: Breslow thickness, infiltrating BCL-2 expressing lymphocytes, and IL-4 and IL-6 serum levels. Importantly, a decrease in serum GM-CSF seems to be a marker of poor prognosis in patients with early-stage melanomas.},\n\tlanguage = {en},\n\tnumber = {7},\n\turldate = {2024-04-15},\n\tjournal = {Cancers},\n\tauthor = {Diaz-Ramón, Jose Luis and Gardeazabal, Jesus and Izu, Rosa Maria and Garrote, Estibaliz and Rasero, Javier and Apraiz, Aintzane and Penas, Cristina and Seijo, Sandra and Lopez-Saratxaga, Cristina and De La Peña, Pedro Maria and Sanchez-Diaz, Ana and Cancho-Galan, Goikoane and Velasco, Veronica and Sevilla, Arrate and Fernandez, David and Cuenca, Iciar and Cortes, Jesus María and Alonso, Santos and Asumendi, Aintzane and Boyano, María Dolores},\n\tmonth = apr,\n\tyear = {2023},\n\tpages = {2174},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Blockage of STAT3 during epileptogenesis prevents GABAergic loss and imprinting of the epileptic state.\n \n \n \n \n\n\n \n Martín-Suárez, S.; Cortes, J. M.; and Bonifazi, P.\n\n\n \n\n\n\n Brain, 146(8): 3416–3430. August 2023.\n \n\n\n\n
\n\n\n\n \n \n $\"Blockage$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{martin-suarez_blockage_2023,\n\ttitle = {Blockage of {STAT3} during epileptogenesis prevents {GABAergic} loss and imprinting of the epileptic state},\n\tvolume = {146},\n\tcopyright = {https://creativecommons.org/licenses/by-nc/4.0/},\n\tissn = {0006-8950, 1460-2156},\n\turl = {https://academic.oup.com/brain/article/146/8/3416/7056474},\n\tdoi = {10.1093/brain/awad055},\n\tabstract = {Abstract\n            Epilepsy, characterized by recurrent unprovoked seizures resulting from a wide variety of causes, is one of the world’s most prominent neurological disabilities. Seizures, which are an expression of neuronal network dysfunction, occur in a positive feedback loop of concomitant factors, including neuro-inflammatory responses, where seizures generate more seizures. Among other pathways involved in inflammatory responses, the JAK/STAT signalling pathway has been proposed to participate in epilepsy.\n            Here, we tested an in vitro model of temporal lobe epilepsy, with the hypothesis that acute blockage of STAT3-phosphorylation during epileptogenesis would prevent structural damage in the hippocampal circuitry and the imprinting of both neural epileptic activity and inflammatory glial states. We performed calcium imaging of spontaneous circuit dynamics in organotypic hippocampal slices previously exposed to epileptogenic conditions through the blockage of GABAergic synaptic transmission.\n            Epileptogenic conditions lead to epileptic dynamics imprinted on circuits in terms of increased neuronal firing and circuit synchronization, increased correlated activity in neuronal pairs and decreased complexity in synchronization patterns. Acute blockage of the STAT3-phosphorylation during epileptogenesis prevented the imprinting of epileptic activity patterns, general cell loss, loss of GABAergic neurons and the persistence of reactive glial states. This work provides mechanistic evidence that blocking the STAT3 signalling pathway during epileptogenesis can prevent patho-topological persistent reorganization of neuro-glial circuits.},\n\tlanguage = {en},\n\tnumber = {8},\n\turldate = {2024-04-15},\n\tjournal = {Brain},\n\tauthor = {Martín-Suárez, Soraya and Cortes, Jesús María and Bonifazi, Paolo},\n\tmonth = aug,\n\tyear = {2023},\n\tpages = {3416--3430},\n}\n\n\n\n\n\n\n\n

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\n \n\n \n \n \n \n \n \n The Neurogenetics of Functional Connectivity Alterations in Autism: Insights From Subtyping in 657 Individuals.\n \n \n \n \n\n\n \n Rasero, J.; Jimenez-Marin, A.; Diez, I.; Toro, R.; Hasan, M. T.; and Cortes, J. M.\n\n\n \n\n\n\n Biological Psychiatry, 94(10): 804–813. November 2023.\n \n\n\n\n
\n\n\n\n \n \n $\"The$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{rasero_neurogenetics_2023,\n\ttitle = {The {Neurogenetics} of {Functional} {Connectivity} {Alterations} in {Autism}: {Insights} {From} {Subtyping} in 657 {Individuals}},\n\tvolume = {94},\n\tissn = {00063223},\n\tshorttitle = {The {Neurogenetics} of {Functional} {Connectivity} {Alterations} in {Autism}},\n\turl = {https://linkinghub.elsevier.com/retrieve/pii/S0006322323012301},\n\tdoi = {10.1016/j.biopsych.2023.04.014},\n\tlanguage = {en},\n\tnumber = {10},\n\turldate = {2024-04-15},\n\tjournal = {Biological Psychiatry},\n\tauthor = {Rasero, Javier and Jimenez-Marin, Antonio and Diez, Ibai and Toro, Roberto and Hasan, Mazahir T. and Cortes, Jesus M.},\n\tmonth = nov,\n\tyear = {2023},\n\tpages = {804--813},\n}\n\n\n\n\n\n\n\n

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\n \n 2022\n \n \n (6)\n \n \n

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\n \n\n \n \n \n \n \n \n High-order functional redundancy in ageing explained via alterations in the connectome in a whole-brain model.\n \n \n \n \n\n\n \n Gatica, M.; E. Rosas, F.; A. M. Mediano, P.; Diez, I.; P. Swinnen, S.; Orio, P.; Cofré, R.; and M. Cortes, J.\n\n\n \n\n\n\n PLOS Computational Biology, 18(9): e1010431. September 2022.\n \n\n\n\n
\n\n\n\n \n \n $\"High-order$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{gatica_high-order_2022,\n\ttitle = {High-order functional redundancy in ageing explained via alterations in the connectome in a whole-brain model},\n\tvolume = {18},\n\tissn = {1553-7358},\n\turl = {https://dx.plos.org/10.1371/journal.pcbi.1010431},\n\tdoi = {10.1371/journal.pcbi.1010431},\n\tabstract = {The human brain generates a rich repertoire of spatio-temporal activity patterns, which support a wide variety of motor and cognitive functions. These patterns of activity change with age in a multi-factorial manner. One of these factors is the variations in the brain’s connectomics that occurs along the lifespan. However, the precise relationship between high-order functional interactions and connnectomics, as well as their variations with age are largely unknown, in part due to the absence of mechanistic models that can efficiently map brain connnectomics to functional connectivity in aging. To investigate this issue, we have built a neurobiologically-realistic whole-brain computational model using both anatomical and functional MRI data from 161 participants ranging from 10 to 80 years old. We show that the differences in high-order functional interactions between age groups can be largely explained by variations in the connectome. Based on this finding, we propose a simple neurodegeneration model that is representative of normal physiological aging. As such, when applied to connectomes of young participant it reproduces the age-variations that occur in the high-order structure of the functional data. Overall, these results begin to disentangle the mechanisms by which structural changes in the connectome lead to functional differences in the ageing brain. Our model can also serve as a starting point for modeling more complex forms of pathological ageing or cognitive deficits.},\n\tlanguage = {en},\n\tnumber = {9},\n\turldate = {2024-04-15},\n\tjournal = {PLOS Computational Biology},\n\tauthor = {Gatica, Marilyn and E. Rosas, Fernando and A. M. Mediano, Pedro and Diez, Ibai and P. Swinnen, Stephan and Orio, Patricio and Cofré, Rodrigo and M. Cortes, Jesus},\n\teditor = {Battaglia, Demian},\n\tmonth = sep,\n\tyear = {2022},\n\tpages = {e1010431},\n}\n\n\n\n\n\n\n\n

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\n \n\n \n \n \n \n \n \n Heart-brain synchronization breakdown in Parkinson’s disease.\n \n \n \n \n\n\n \n Iniguez, M.; Jimenez-Marin, A.; Erramuzpe, A.; Acera, M.; Tijero, B.; Murueta-Goyena, A.; Del Pino, R.; Fernandez, T.; Carmona‑Abellan, M.; Cabrera-Zubizarreta, A.; Gómez‑Esteban, J. C.; Cortes, J. M.; and Gabilondo, I.\n\n\n \n\n\n\n npj Parkinson's Disease, 8(1): 64. May 2022.\n \n\n\n\n
\n\n\n\n \n \n $\"Heart-brain$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{iniguez_heart-brain_2022,\n\ttitle = {Heart-brain synchronization breakdown in {Parkinson}’s disease},\n\tvolume = {8},\n\tissn = {2373-8057},\n\turl = {https://www.nature.com/articles/s41531-022-00323-w},\n\tdoi = {10.1038/s41531-022-00323-w},\n\tabstract = {Abstract\n            Heart rate variability (HRV) abnormalities are potential early biomarkers in Parkinson’s disease (PD) but their relationship with central autonomic network (CAN) activity is not fully understood. We analyzed the synchronization between HRV and brain activity in 31 PD patients and 21 age-matched healthy controls using blood-oxygen-level-dependent (BOLD) signals from resting-state functional brain MRI and HRV metrics from finger plethysmography recorded for 7.40 min. We additionally quantified autonomic symptoms (SCOPA-AUT) and objective autonomic cardiovascular parameters (blood pressure and heart rate) during deep breathing, Valsalva, and head-up tilt, which were used to classify the clinical severity of dysautonomia. We evaluated HRV and BOLD signals synchronization (HRV-BOLD-sync) with Pearson lagged cross-correlations and Fisher’s statistics for combining window-length-dependent HRV-BOLD-Sync Maps and assessed their association with clinical dysautonomia. HRV-BOLD-sync was lower significantly in PD than in controls in various brain regions within CAN or in networks involved in autonomic modulation. Moreover, heart-brain synchronization index (HBSI), which quantifies heart-brain synchronization at a single-subject level, showed an inverse exposure–response relationship with dysautonomia severity, finding the lowest HBSI in patients with severe dysautonomia, followed by moderate, mild, and, lastly, controls. Importantly, HBSI was associated in PD, but not in controls, with Valsalva pressure recovery time (sympathetic), deep breathing E/I ratio (cardiovagal), and SCOPA-AUT. Our findings support the existence of heart-brain de-synchronization in PD with an impact on clinically relevant autonomic outcomes.},\n\tlanguage = {en},\n\tnumber = {1},\n\turldate = {2024-04-15},\n\tjournal = {npj Parkinson's Disease},\n\tauthor = {Iniguez, Martin and Jimenez-Marin, Antonio and Erramuzpe, Asier and Acera, Marian and Tijero, Beatriz and Murueta-Goyena, Ane and Del Pino, Rocio and Fernandez, Tamara and Carmona‑Abellan, Mar and Cabrera-Zubizarreta, Alberto and Gómez‑Esteban, Juan Carlos and Cortes, Jesus M. and Gabilondo, Inigo},\n\tmonth = may,\n\tyear = {2022},\n\tpages = {64},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Multimodal and multidomain lesion network mapping enhances prediction of sensorimotor behavior in stroke patients.\n \n \n \n \n\n\n \n Jimenez-Marin, A.; De Bruyn, N.; Gooijers, J.; Llera, A.; Meyer, S.; Alaerts, K.; Verheyden, G.; Swinnen, S. P.; and Cortes, J. M.\n\n\n \n\n\n\n Scientific Reports, 12(1): 22400. December 2022.\n \n\n\n\n
\n\n\n\n \n \n $\"Multimodal$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{jimenez-marin_multimodal_2022,\n\ttitle = {Multimodal and multidomain lesion network mapping enhances prediction of sensorimotor behavior in stroke patients},\n\tvolume = {12},\n\tissn = {2045-2322},\n\turl = {https://www.nature.com/articles/s41598-022-26945-x},\n\tdoi = {10.1038/s41598-022-26945-x},\n\tabstract = {Abstract\n            Beyond the characteristics of a brain lesion, such as its etiology, size or location, lesion network mapping (LNM) has shown that similar symptoms after a lesion reflects similar dis-connectivity patterns, thereby linking symptoms to brain networks. Here, we extend LNM by using a multimodal strategy, combining functional and structural networks from 1000 healthy participants in the Human Connectome Project. We apply multimodal LNM to a cohort of 54 stroke patients with the aim of predicting sensorimotor behavior, as assessed through a combination of motor and sensory tests. Results are two-fold. First, multimodal LNM reveals that the functional modality contributes more than the structural one in the prediction of sensorimotor behavior. Second, when looking at each modality individually, the performance of the structural networks strongly depended on whether sensorimotor performance was corrected for lesion size, thereby eliminating the effect that larger lesions generally produce more severe sensorimotor impairment. In contrast, functional networks provided similar performance regardless of whether or not the effect of lesion size was removed. Overall, these results support the extension of LNM to its multimodal form, highlighting the synergistic and additive nature of different types of network modalities, and their corresponding influence on behavioral performance after brain injury.},\n\tlanguage = {en},\n\tnumber = {1},\n\turldate = {2024-04-15},\n\tjournal = {Scientific Reports},\n\tauthor = {Jimenez-Marin, Antonio and De Bruyn, Nele and Gooijers, Jolien and Llera, Alberto and Meyer, Sarah and Alaerts, Kaat and Verheyden, Geert and Swinnen, Stephan P. and Cortes, Jesus M.},\n\tmonth = dec,\n\tyear = {2022},\n\tpages = {22400},\n}\n\n\n\n\n\n\n\n

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\n \n\n \n \n \n \n \n \n White matter integrity changes and neurocognitive functioning in adult-late onset DM1: a follow-up DTI study.\n \n \n \n \n\n\n \n Labayru, G.; Camino, B.; Jimenez-Marin, A.; Garmendia, J.; Villanua, J.; Zulaica, M.; Cortes, J. M.; López De Munain, A.; and Sistiaga, A.\n\n\n \n\n\n\n Scientific Reports, 12(1): 3988. March 2022.\n \n\n\n\n
\n\n\n\n \n \n $\"White$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{labayru_white_2022,\n\ttitle = {White matter integrity changes and neurocognitive functioning in adult-late onset {DM1}: a follow-up {DTI} study},\n\tvolume = {12},\n\tissn = {2045-2322},\n\tshorttitle = {White matter integrity changes and neurocognitive functioning in adult-late onset {DM1}},\n\turl = {https://www.nature.com/articles/s41598-022-07820-1},\n\tdoi = {10.1038/s41598-022-07820-1},\n\tabstract = {Abstract\n            Myotonic Dystrophy Type 1 (DM1) is a multisystemic disease that affects gray and white matter (WM) tissues. WM changes in DM1 include increased hyperintensities and altered tract integrity distributed in a widespread manner. However, the precise temporal and spatial progression of the changes are yet undetermined. MRI data were acquired from 8 adult- and late-onset DM1 patients and 10 healthy controls (HC) at two different timepoints over 9.06 years. Fractional anisotropy (FA) and mean diffusivity (MD) variations were assessed with Tract-Based Spatial Statistics. Transversal and longitudinal intra- and intergroup analyses were conducted, along with correlation analyses with clinical and neuropsychological data. At baseline, reduced FA and increased MD values were found in patients in the uncinate, anterior-thalamic, fronto-occipital, and longitudinal tracts. At follow-up, the WM disconnection was shown to have spread from the frontal part to the rest of the tracts in the brain. Furthermore, WM lesion burden was negatively correlated with FA values, while visuo-construction and intellectual functioning were positively correlated with global and regional FA values at follow-up. DM1 patients showed a pronounced WM integrity loss over time compared to HC, with a neurodegeneration pattern that suggests a progressive anterior–posterior disconnection. The visuo-construction domain stands out as the most sensitive neuropsychological measure for WM microstructural impairment.},\n\tlanguage = {en},\n\tnumber = {1},\n\turldate = {2024-04-15},\n\tjournal = {Scientific Reports},\n\tauthor = {Labayru, Garazi and Camino, Borja and Jimenez-Marin, Antonio and Garmendia, Joana and Villanua, Jorge and Zulaica, Miren and Cortes, Jesus M. and López De Munain, Adolfo and Sistiaga, Andone},\n\tmonth = mar,\n\tyear = {2022},\n\tpages = {3988},\n}\n\n\n\n\n\n\n\n

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\n \n\n \n \n \n \n \n \n The structure of anticorrelated networks in the human brain.\n \n \n \n \n\n\n \n Martinez-Gutierrez, E.; Jimenez-Marin, A.; Stramaglia, S.; and Cortes, J. M.\n\n\n \n\n\n\n Frontiers in Network Physiology, 2: 946380. November 2022.\n \n\n\n\n
\n\n\n\n \n \n $\"The$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{martinez-gutierrez_structure_2022,\n\ttitle = {The structure of anticorrelated networks in the human brain},\n\tvolume = {2},\n\tissn = {2674-0109},\n\turl = {https://www.frontiersin.org/articles/10.3389/fnetp.2022.946380/full},\n\tdoi = {10.3389/fnetp.2022.946380},\n\tabstract = {During the performance of a specific task--or at rest--, the activity of different brain regions shares statistical dependencies that reflect functional connections. While these relationships have been studied intensely for positively correlated networks, considerably less attention has been paid to negatively correlated networks, a. k.a. anticorrelated networks (ACNs). Although the most celebrated of all ACNs is the default mode network (DMN), and has even been extensively studied in health and disease, for systematically all ACNs other than DMN, there is no comprehensive study yet. Here, we have addressed this issue by making use of three neuroimaging data sets: one of N = 192 healthy young adults to fully describe ACN, another of N = 40 subjects to compare ACN between two groups of young and old participants, and another of N = 1,000 subjects from the Human Connectome Project to evaluate the association between ACN and cognitive scores. We first provide a comprehensive description of the anatomical composition of all ACNs, each of which participated in distinct resting-state networks (RSNs). In terms of participation ranking, from highest to the lowest, the major anticorrelated brain areas are the precuneus, the anterior supramarginal gyrus and the central opercular cortex. Next, by evaluating a more detailed structure of ACN, we show it is possible to find significant differences in ACN between specific conditions, in particular, by comparing groups of young and old participants. Our main finding is that of increased anticorrelation for cerebellar interactions in older subjects. Finally, in the voxel-level association study with cognitive scores, we show that ACN has multiple clusters of significance, clusters that are different from those obtained from positive correlated networks, indicating a functional cognitive meaning of ACN. Overall, our results give special relevance to ACN and suggest their use to disentangle unknown alterations in certain conditions, as could occur in early-onset neurodegenerative diseases or in some psychiatric conditions.},\n\turldate = {2024-04-15},\n\tjournal = {Frontiers in Network Physiology},\n\tauthor = {Martinez-Gutierrez, Endika and Jimenez-Marin, Antonio and Stramaglia, Sebastiano and Cortes, Jesus M.},\n\tmonth = nov,\n\tyear = {2022},\n\tpages = {946380},\n}\n\n\n\n\n\n\n\n

\n

\n\n\n

\n During the performance of a specific task–or at rest–, the activity of different brain regions shares statistical dependencies that reflect functional connections. While these relationships have been studied intensely for positively correlated networks, considerably less attention has been paid to negatively correlated networks, a. k.a. anticorrelated networks (ACNs). Although the most celebrated of all ACNs is the default mode network (DMN), and has even been extensively studied in health and disease, for systematically all ACNs other than DMN, there is no comprehensive study yet. Here, we have addressed this issue by making use of three neuroimaging data sets: one of N = 192 healthy young adults to fully describe ACN, another of N = 40 subjects to compare ACN between two groups of young and old participants, and another of N = 1,000 subjects from the Human Connectome Project to evaluate the association between ACN and cognitive scores. We first provide a comprehensive description of the anatomical composition of all ACNs, each of which participated in distinct resting-state networks (RSNs). In terms of participation ranking, from highest to the lowest, the major anticorrelated brain areas are the precuneus, the anterior supramarginal gyrus and the central opercular cortex. Next, by evaluating a more detailed structure of ACN, we show it is possible to find significant differences in ACN between specific conditions, in particular, by comparing groups of young and old participants. Our main finding is that of increased anticorrelation for cerebellar interactions in older subjects. Finally, in the voxel-level association study with cognitive scores, we show that ACN has multiple clusters of significance, clusters that are different from those obtained from positive correlated networks, indicating a functional cognitive meaning of ACN. Overall, our results give special relevance to ACN and suggest their use to disentangle unknown alterations in certain conditions, as could occur in early-onset neurodegenerative diseases or in some psychiatric conditions.\n

\n\n\n

\n \n\n \n \n \n \n \n \n Brain Mapping of Behavioral Domains Using Multi-Scale Networks and Canonical Correlation Analysis.\n \n \n \n \n\n\n \n Fernandez-Iriondo, I.; Jimenez-Marin, A.; Sierra, B.; Aginako, N.; Bonifazi, P.; and Cortes, J. M.\n\n\n \n\n\n\n Frontiers in Neuroscience, 16. June 2022.\n \n\n\n\n
\n\n\n\n \n \n $\"Brain$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

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@article{fernandez-iriondo_brain_2022,\n\ttitle = {Brain {Mapping} of {Behavioral} {Domains} {Using} {Multi}-{Scale} {Networks} and {Canonical} {Correlation} {Analysis}},\n\tvolume = {16},\n\tissn = {1662-453X},\n\turl = {https://www.frontiersin.org/journals/neuroscience/articles/10.3389/fnins.2022.889725/full},\n\tdoi = {10.3389/fnins.2022.889725},\n\tabstract = {{\\textless}p{\\textgreater}Simultaneous mapping of multiple behavioral domains into brain networks remains a major challenge. Here, we shed some light on this problem by employing a combination of machine learning, structural and functional brain networks at different spatial resolutions (also known as scales), together with performance scores across multiple neurobehavioral domains, including sensation, motor skills, and cognition. Provided by the Human Connectome Project, we make use of three cohorts: 640 participants for model training, 160 subjects for validation, and 200 subjects for model performance testing thus enhancing prediction generalization. Our modeling consists of two main stages, namely dimensionality reduction in brain network features at multiple scales, followed by canonical correlation analysis, which determines an optimal linear combination of connectivity features to predict multiple behavioral performance scores. To assess the differences in the predictive power of each modality, we separately applied three different strategies: structural unimodal, functional unimodal, and multimodal, that is, structural in combination with functional features of the brain network. Our results show that the multimodal association outperforms any of the unimodal analyses. Then, to answer which human brain structures were most involved in predicting multiple behavioral scores, we simulated different synthetic scenarios in which in each case we completely deleted a brain structure or a complete resting state network, and recalculated performance in its absence. In deletions, we found critical structures to affect performance when predicting single behavioral domains, but this occurred in a lesser manner for prediction of multi-domain behavior. Overall, our results confirm that although there are synergistic contributions between brain structure and function that enhance behavioral prediction, brain networks may also be mutually redundant in predicting multidomain behavior, such that even after deletion of a structure, the connectivity of the others can compensate for its lack in predicting behavior.{\\textless}/p{\\textgreater}},\n\tlanguage = {English},\n\turldate = {2024-04-14},\n\tjournal = {Frontiers in Neuroscience},\n\tauthor = {Fernandez-Iriondo, Izaro and Jimenez-Marin, Antonio and Sierra, Basilio and Aginako, Naiara and Bonifazi, Paolo and Cortes, Jesus M.},\n\tmonth = jun,\n\tyear = {2022},\n\tkeywords = {Behavior, Brain network mapping, Multi-scale networks, canonical correlation analysis, diffusion MRI, functional MRI, machine learning},\n}\n\n\n\n\n\n\n\n

\n

\n\n\n

\n \\textlessp\\textgreaterSimultaneous mapping of multiple behavioral domains into brain networks remains a major challenge. Here, we shed some light on this problem by employing a combination of machine learning, structural and functional brain networks at different spatial resolutions (also known as scales), together with performance scores across multiple neurobehavioral domains, including sensation, motor skills, and cognition. Provided by the Human Connectome Project, we make use of three cohorts: 640 participants for model training, 160 subjects for validation, and 200 subjects for model performance testing thus enhancing prediction generalization. Our modeling consists of two main stages, namely dimensionality reduction in brain network features at multiple scales, followed by canonical correlation analysis, which determines an optimal linear combination of connectivity features to predict multiple behavioral performance scores. To assess the differences in the predictive power of each modality, we separately applied three different strategies: structural unimodal, functional unimodal, and multimodal, that is, structural in combination with functional features of the brain network. Our results show that the multimodal association outperforms any of the unimodal analyses. Then, to answer which human brain structures were most involved in predicting multiple behavioral scores, we simulated different synthetic scenarios in which in each case we completely deleted a brain structure or a complete resting state network, and recalculated performance in its absence. In deletions, we found critical structures to affect performance when predicting single behavioral domains, but this occurred in a lesser manner for prediction of multi-domain behavior. Overall, our results confirm that although there are synergistic contributions between brain structure and function that enhance behavioral prediction, brain networks may also be mutually redundant in predicting multidomain behavior, such that even after deletion of a structure, the connectivity of the others can compensate for its lack in predicting behavior.\\textless/p\\textgreater\n

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\n \n 2021\n \n \n (9)\n \n \n

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\n \n\n \n \n \n \n \n \n Visual dysfunction is associated with cognitive impairment in Parkinson's disease.\n \n \n \n \n\n\n \n Del Pino, R.; Acera, M.; Murueta-Goyena, A.; Lucas-Jiménez, O.; Ojeda, N.; Ibarretxe-Bilbao, N.; Peña, J.; Reyero, P.; Cortés, J.; Tijero, B.; Galdós, M.; Gómez-Esteban, J. C.; and Gabilondo, I.\n\n\n \n\n\n\n Parkinsonism & Related Disorders, 92: 22–25. November 2021.\n \n\n\n\n
\n\n\n\n \n \n $\"Visual$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{del_pino_visual_2021,\n\ttitle = {Visual dysfunction is associated with cognitive impairment in {Parkinson}'s disease},\n\tvolume = {92},\n\tissn = {13538020},\n\turl = {https://linkinghub.elsevier.com/retrieve/pii/S1353802021003606},\n\tdoi = {10.1016/j.parkreldis.2021.10.005},\n\tlanguage = {en},\n\turldate = {2024-04-15},\n\tjournal = {Parkinsonism \\& Related Disorders},\n\tauthor = {Del Pino, Rocío and Acera, Marian and Murueta-Goyena, Ane and Lucas-Jiménez, Olaia and Ojeda, Natalia and Ibarretxe-Bilbao, Naroa and Peña, Javier and Reyero, Paula and Cortés, Jesús and Tijero, Beatriz and Galdós, Marta and Gómez-Esteban, Juan Carlos and Gabilondo, Iñigo},\n\tmonth = nov,\n\tyear = {2021},\n\tpages = {22--25},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Individual‐based morphological brain network organization and its association with autistic symptoms in young children with autism spectrum disorder.\n \n \n \n \n\n\n \n He, C.; Cortes, J. M.; Kang, X.; Cao, J.; Chen, H.; Guo, X.; Wang, R.; Kong, L.; Huang, X.; Xiao, J.; Shan, X.; Feng, R.; Chen, H.; and Duan, X.\n\n\n \n\n\n\n Human Brain Mapping, 42(10): 3282–3294. July 2021.\n \n\n\n\n
\n\n\n\n \n \n $\"Individual‐based$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{he_individualbased_2021,\n\ttitle = {Individual‐based morphological brain network organization and its association with autistic symptoms in young children with autism spectrum disorder},\n\tvolume = {42},\n\tissn = {1065-9471, 1097-0193},\n\turl = {https://onlinelibrary.wiley.com/doi/10.1002/hbm.25434},\n\tdoi = {10.1002/hbm.25434},\n\tabstract = {Abstract\n            Individual‐based morphological brain networks built from T1‐weighted magnetic resonance imaging (MRI) reflect synchronous maturation intensities between anatomical regions at the individual level. Autism spectrum disorder (ASD) is a socio‐cognitive and neurodevelopmental disorder with high neuroanatomical heterogeneity, but the specific patterns of morphological networks in ASD remain largely unexplored at the individual level. In this study, individual‐based morphological networks were constructed by using high‐resolution structural MRI data from 40 young children with ASD (age range: 2–8 years) and 38 age‐, gender‐, and handedness‐matched typically developing children (TDC). Measurements were recorded as threefold. Results showed that compared with TDC, young children with ASD exhibited lower values of small‐worldness (i.e., σ) of individual‐level morphological brain networks, increased morphological connectivity in cortico‐striatum‐thalamic‐cortical (CSTC) circuitry, and decreased morphological connectivity in the cortico‐cortical network. In addition, morphological connectivity abnormalities can predict the severity of social communication deficits in young children with ASD, thus confirming an associational impact at the behavioral level. These findings suggest that the morphological brain network in the autistic developmental brain is inefficient in segregating and distributing information. The results also highlight the crucial role of abnormal morphological connectivity patterns in the socio‐cognitive deficits of ASD and support the possible use of the aberrant developmental patterns of morphological brain networks in revealing new clinically‐relevant biomarkers for ASD.},\n\tlanguage = {en},\n\tnumber = {10},\n\turldate = {2024-04-15},\n\tjournal = {Human Brain Mapping},\n\tauthor = {He, Changchun and Cortes, Jesus M. and Kang, Xiaodong and Cao, Jing and Chen, Heng and Guo, Xiaonan and Wang, Ruishi and Kong, Lingyin and Huang, Xinyue and Xiao, Jinming and Shan, Xiaolong and Feng, Rui and Chen, Huafu and Duan, Xujun},\n\tmonth = jul,\n\tyear = {2021},\n\tpages = {3282--3294},\n}\n\n\n\n\n\n\n\n

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\n \n\n \n \n \n \n \n \n High-Order Interdependencies in the Aging Brain.\n \n \n \n \n\n\n \n Gatica, M.; Cofré, R.; Mediano, P. A.; Rosas, F. E.; Orio, P.; Diez, I.; Swinnen, S. P.; and Cortes, J. M.\n\n\n \n\n\n\n Brain Connectivity, 11(9): 734–744. November 2021.\n \n\n\n\n
\n\n\n\n \n \n $\"High-Order$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{gatica_high-order_2021,\n\ttitle = {High-{Order} {Interdependencies} in the {Aging} {Brain}},\n\tvolume = {11},\n\tcopyright = {https://www.liebertpub.com/nv/resources-tools/text-and-data-mining-policy/121/},\n\tissn = {2158-0014, 2158-0022},\n\turl = {https://www.liebertpub.com/doi/10.1089/brain.2020.0982},\n\tdoi = {10.1089/brain.2020.0982},\n\tlanguage = {en},\n\tnumber = {9},\n\turldate = {2024-04-15},\n\tjournal = {Brain Connectivity},\n\tauthor = {Gatica, Marilyn and Cofré, Rodrigo and Mediano, Pedro A.M. and Rosas, Fernando E. and Orio, Patricio and Diez, Ibai and Swinnen, Stephan P. and Cortes, Jesus M.},\n\tmonth = nov,\n\tyear = {2021},\n\tpages = {734--744},\n}\n\n\n\n\n\n\n\n

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\n \n\n \n \n \n \n \n \n Transcriptional signatures of synaptic vesicle genes define myotonic dystrophy type I neurodegeneration.\n \n \n \n \n\n\n \n Jimenez‐Marin, A.; Diez, I.; Labayru, G.; Sistiaga, A.; Caballero, M. C.; Andres‐Benito, P.; Sepulcre, J.; Ferrer, I.; Lopez De Munain, A.; and Cortes, J. M.\n\n\n \n\n\n\n Neuropathology and Applied Neurobiology, 47(7): 1092–1108. December 2021.\n \n\n\n\n
\n\n\n\n \n \n $\"Transcriptional$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{jimenezmarin_transcriptional_2021,\n\ttitle = {Transcriptional signatures of synaptic vesicle genes define myotonic dystrophy type {I} neurodegeneration},\n\tvolume = {47},\n\tissn = {0305-1846, 1365-2990},\n\turl = {https://onlinelibrary.wiley.com/doi/10.1111/nan.12725},\n\tdoi = {10.1111/nan.12725},\n\tabstract = {Abstract\n            \n              Aim\n              To delineate the neurogenetic profiles of brain degeneration patterns in myotonic dystrophy type I (DM1).\n            \n            \n              Methods\n              In two cohorts of DM1 patients, brain maps of volume loss (VL) and neuropsychological deficits (NDs) were intersected to large‐scale transcriptome maps provided by the Allen Human Brain Atlas (AHBA). For validation, neuropathological and RNA analyses were performed in a small series of DM1 brain samples.\n            \n            \n              Results\n              \n                Twofold: (1) From a list of preselected hypothesis‐driven genes, confirmatory analyses found that three genes play a major role in brain degeneration: dystrophin (\n                DMD)\n                , alpha‐synuclein (\n                SNCA)\n                 and the microtubule‐associated protein tau (\n                MAPT)\n                . Neuropathological analyses confirmed a highly heterogeneous Tau‐pathology in DM1, different to the one in Alzheimer's disease. (2) Exploratory analyses revealed gene clusters enriched for key biological processes in the central nervous system, such as synaptic vesicle recycling, localization, endocytosis and exocytosis, and the serotonin and dopamine neurotransmitter pathways. RNA analyses confirmed synaptic vesicle dysfunction.\n              \n            \n            \n              Conclusions\n              The combination of large‐scale transcriptome interactions with brain imaging and cognitive function sheds light on the neurobiological mechanisms of brain degeneration in DM1 that might help define future therapeutic strategies and research into this condition.},\n\tlanguage = {en},\n\tnumber = {7},\n\turldate = {2024-04-15},\n\tjournal = {Neuropathology and Applied Neurobiology},\n\tauthor = {Jimenez‐Marin, Antonio and Diez, Ibai and Labayru, Garazi and Sistiaga, Andone and Caballero, Maria C. and Andres‐Benito, Pol and Sepulcre, Jorge and Ferrer, Isidro and Lopez De Munain, Adolfo and Cortes, Jesus M.},\n\tmonth = dec,\n\tyear = {2021},\n\tpages = {1092--1108},\n}\n\n\n\n\n\n\n\n\n\n\n\n

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\n \n\n \n \n \n \n \n \n A global analysis of the reconstitution of PTEN function by translational readthrough of PTEN pathogenic premature termination codons.\n \n \n \n \n\n\n \n Luna, S.; Torices, L.; Mingo, J.; Amo, L.; Rodríguez‐Escudero, I.; Ruiz‐Ibarlucea, P.; Erramuzpe, A.; Cortés, J. M.; Tejada, M. I.; Molina, M.; Nunes‐Xavier, C. E.; López, J. I.; Cid, V. J.; and Pulido, R.\n\n\n \n\n\n\n Human Mutation, 42(5): 551–566. May 2021.\n \n\n\n\n
\n\n\n\n \n \n $\"A$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{luna_global_2021,\n\ttitle = {A global analysis of the reconstitution of {PTEN} function by translational readthrough of \\textit{{PTEN}} pathogenic premature termination codons},\n\tvolume = {42},\n\tissn = {1059-7794, 1098-1004},\n\turl = {https://onlinelibrary.wiley.com/doi/10.1002/humu.24186},\n\tdoi = {10.1002/humu.24186},\n\tlanguage = {en},\n\tnumber = {5},\n\turldate = {2024-04-15},\n\tjournal = {Human Mutation},\n\tauthor = {Luna, Sandra and Torices, Leire and Mingo, Janire and Amo, Laura and Rodríguez‐Escudero, Isabel and Ruiz‐Ibarlucea, Pablo and Erramuzpe, Asier and Cortés, Jesús M. and Tejada, María I. and Molina, María and Nunes‐Xavier, Caroline E. and López, José I. and Cid, Víctor J. and Pulido, Rafael},\n\tmonth = may,\n\tyear = {2021},\n\tpages = {551--566},\n}\n\n\n\n\n\n\n\n

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\n \n\n \n \n \n \n \n \n Retinal Thickness Predicts the Risk of Cognitive Decline in Parkinson Disease.\n \n \n \n \n\n\n \n Murueta‐Goyena, A.; Del Pino, R.; Galdós, M.; Arana, B.; Acera, M.; Carmona‐Abellán, M.; Fernández‐Valle, T.; Tijero, B.; Lucas‐Jiménez, O.; Ojeda, N.; Ibarretxe‐Bilbao, N.; Peña, J.; Cortes, J.; Ayala, U.; Barrenechea, M.; Gómez‐Esteban, J. C.; and Gabilondo, I.\n\n\n \n\n\n\n Annals of Neurology, 89(1): 165–176. January 2021.\n \n\n\n\n
\n\n\n\n \n \n $\"Retinal$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{muruetagoyena_retinal_2021,\n\ttitle = {Retinal {Thickness} {Predicts} the {Risk} of {Cognitive} {Decline} in {Parkinson} {Disease}},\n\tvolume = {89},\n\tissn = {0364-5134, 1531-8249},\n\turl = {https://onlinelibrary.wiley.com/doi/10.1002/ana.25944},\n\tdoi = {10.1002/ana.25944},\n\tabstract = {Objective\n              This study was undertaken to analyze longitudinal changes of retinal thickness and their predictive value as biomarkers of disease progression in idiopathic Parkinson's disease (iPD).\n            \n            \n              Methods\n              \n                Patients with Lewy body diseases were enrolled and prospectively evaluated at 3 years, including patients with iPD (n = 42), dementia with Lewy bodies (n = 4), E46K‐\n                SNCA\n                mutation carriers (n = 4), and controls (n = 17). All participants underwent Spectralis retinal optical coherence tomography and Montreal Cognitive Assessment, and Unified Parkinson's Disease Rating Scale score was obtained in patients. Macular ganglion cell–inner plexiform layer complex (GCIPL) and peripapillary retinal nerve fiber layer (pRNFL) thickness reduction rates were estimated with linear mixed models. Risk ratios were calculated to evaluate the association between baseline GCIPL and pRNFL thicknesses and the risk of subsequent cognitive and motor worsening, using clinically meaningful cutoffs.\n              \n            \n            \n              Results\n              \n                GCIPL thickness in the parafoveal region (1‐ to 3‐mm ring) presented the largest reduction rate. The annualized atrophy rate was 0.63μm in iPD patients and 0.23μm in controls (\n                p\n                 {\\textless} 0.0001). iPD patients with lower parafoveal GCIPL and pRNFL thickness at baseline presented an increased risk of cognitive decline at 3 years (relative risk [RR] = 3.49, 95\\% confidence interval [CI] = 1.10–11.1,\n                p\n                = 0.03 and RR = 3.28, 95\\% CI = 1.03–10.45,\n                p\n                = 0.045, respectively). We did not identify significant associations between retinal thickness and motor deterioration.\n              \n            \n            \n              Interpretation\n              Our results provide evidence of the potential use of optical coherence tomography–measured parafoveal GCIPL thickness to monitor neurodegeneration and to predict the risk of cognitive worsening over time in iPD. ANN NEUROL 2021;89:165–176},\n\tlanguage = {en},\n\tnumber = {1},\n\turldate = {2024-04-15},\n\tjournal = {Annals of Neurology},\n\tauthor = {Murueta‐Goyena, Ane and Del Pino, Rocío and Galdós, Marta and Arana, Begoña and Acera, Marian and Carmona‐Abellán, Mar and Fernández‐Valle, Tamara and Tijero, Beatriz and Lucas‐Jiménez, Olaia and Ojeda, Natalia and Ibarretxe‐Bilbao, Naroa and Peña, Javier and Cortes, Jesus and Ayala, Unai and Barrenechea, Maitane and Gómez‐Esteban, Juan Carlos and Gabilondo, Iñigo},\n\tmonth = jan,\n\tyear = {2021},\n\tpages = {165--176},\n}\n\n\n\n\n\n\n\n

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\n \n\n \n \n \n \n \n \n A Controlled Thermoalgesic Stimulation Device for Exploring Novel Pain Perception Biomarkers.\n \n \n \n \n\n\n \n Nunez-Ibero, M.; Camino-Pontes, B.; Diez, I.; Erramuzpe, A.; Martinez-Gutierrez, E.; Stramaglia, S.; Alvarez-Cienfuegos, J. O.; and Cortes, J. M.\n\n\n \n\n\n\n IEEE Journal of Biomedical and Health Informatics, 25(8): 2948–2957. August 2021.\n \n\n\n\n
\n\n\n\n \n \n $\"A$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{nunez-ibero_controlled_2021,\n\ttitle = {A {Controlled} {Thermoalgesic} {Stimulation} {Device} for {Exploring} {Novel} {Pain} {Perception} {Biomarkers}},\n\tvolume = {25},\n\tcopyright = {https://ieeexplore.ieee.org/Xplorehelp/downloads/license-information/IEEE.html},\n\tissn = {2168-2194, 2168-2208},\n\turl = {https://ieeexplore.ieee.org/document/9432748/},\n\tdoi = {10.1109/JBHI.2021.3080935},\n\tnumber = {8},\n\turldate = {2024-04-15},\n\tjournal = {IEEE Journal of Biomedical and Health Informatics},\n\tauthor = {Nunez-Ibero, Maider and Camino-Pontes, Borja and Diez, Ibai and Erramuzpe, Asier and Martinez-Gutierrez, Endika and Stramaglia, Sebastiano and Alvarez-Cienfuegos, Javier O. and Cortes, Jesus M.},\n\tmonth = aug,\n\tyear = {2021},\n\tpages = {2948--2957},\n}\n\n\n\n\n\n\n\n

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\n \n\n \n \n \n \n \n \n MMADHC premature termination codons in the pathogenesis of cobalamin D disorder: Potential of translational readthrough reconstitution.\n \n \n \n \n\n\n \n Torices, L.; De Las Heras, J.; Arango-Lasprilla, J. C.; Cortés, J. M.; Nunes-Xavier, C. E.; and Pulido, R.\n\n\n \n\n\n\n Molecular Genetics and Metabolism Reports, 26: 100710. March 2021.\n \n\n\n\n
\n\n\n\n \n \n $\"MMADHC$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{torices_mmadhc_2021,\n\ttitle = {{MMADHC} premature termination codons in the pathogenesis of cobalamin {D} disorder: {Potential} of translational readthrough reconstitution},\n\tvolume = {26},\n\tissn = {22144269},\n\tshorttitle = {{MMADHC} premature termination codons in the pathogenesis of cobalamin {D} disorder},\n\turl = {https://linkinghub.elsevier.com/retrieve/pii/S2214426921000045},\n\tdoi = {10.1016/j.ymgmr.2021.100710},\n\tlanguage = {en},\n\turldate = {2024-04-15},\n\tjournal = {Molecular Genetics and Metabolism Reports},\n\tauthor = {Torices, Leire and De Las Heras, Javier and Arango-Lasprilla, Juan Carlos and Cortés, Jesús M. and Nunes-Xavier, Caroline E. and Pulido, Rafael},\n\tmonth = mar,\n\tyear = {2021},\n\tpages = {100710},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Small variation in dynamic functional connectivity in cerebellar networks.\n \n \n \n \n\n\n \n Fernandez-Iriondo, I.; Jimenez-Marin, A.; Diez, I.; Bonifazi, P.; Swinnen, S. P.; Muñoz, M. A.; and Cortes, J. M.\n\n\n \n\n\n\n Neurocomputing, 461: 751–761. October 2021.\n \n\n\n\n
\n\n\n\n \n \n $\"Small$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n \n \n 1 download\n \n \n\n \n \n \n \n \n \n \n\n \n \n \n \n \n \n \n \n \n \n \n \n \n\n\n\n

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@article{fernandez-iriondo_small_2021,\n\ttitle = {Small variation in dynamic functional connectivity in cerebellar networks},\n\tvolume = {461},\n\tissn = {0925-2312},\n\turl = {https://www.sciencedirect.com/science/article/pii/S0925231221007724},\n\tdoi = {10.1016/j.neucom.2020.09.092},\n\tabstract = {Brain networks can be defined and explored through their connectivity. Here, we analyzed the relationship between structural connectivity (SC) across 2,514 regions that cover the entire brain and brainstem, and their dynamic functional connectivity (DFC). To do so, we focused on a combination of two metrics: the first assesses the degree of SC-DFC similarity -i.e. the extent to which the dynamic functional correlations can be explained by structural pathways-; and the second is the intrinsic variability of the DFC networks over time. Overall, we found that cerebellar networks have a smaller DFC variability than other networks in the brain. Moreover, the internal structure of the cerebellum could be clearly divided in two distinct posterior and anterior parts, the latter also connected to the brainstem. The mechanism to maintain small variability of the DFC in the posterior part of the cerebellum is consistent with another of our findings, namely, that this structure exhibits the highest SC-DFC similarity relative to the other networks studied, i.e. structure constrains the variation in dynamics. By contrast, the anterior part of the cerebellum also exhibits small DFC variability but it has the lowest SC-DFC similarity, suggesting a different mechanism is at play. Because this structure connects to the brainstem, which regulates sleep cycles, cardiac and respiratory functioning, we suggest that such critical functionality drives the low variability in the DFC. Overall, the low variability detected in DFC expands our current knowledge of cerebellar networks, which are extremely rich and complex, participating in a wide range of cognitive functions, from movement control and coordination to executive function or emotional regulation. Moreover, the association between such low variability and structure suggests that differentiated computational principles can be applied in the cerebellum as opposed to other structures, such as the cerebral cortex.},\n\turldate = {2024-04-14},\n\tjournal = {Neurocomputing},\n\tauthor = {Fernandez-Iriondo, Izaro and Jimenez-Marin, Antonio and Diez, Ibai and Bonifazi, Paolo and Swinnen, Stephan P. and Muñoz, Miguel A. and Cortes, Jesus M.},\n\tmonth = oct,\n\tyear = {2021},\n\tkeywords = {Anterior Cerebellum, Dynamic functional connectivity, Posterior Cerebellum, Resting state, Structural connectivity},\n\tpages = {751--761},\n}\n

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\n \n 2020\n \n \n (6)\n \n \n

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\n \n\n \n \n \n \n \n \n Brain Circuit Alterations and Cognitive Disability in Late-Onset Cobalamin D Disorder.\n \n \n \n \n\n\n \n De Las Heras, J.; Diez, I.; Jimenez-Marin, A.; Cabrera, A.; Ramos-Usuga, D.; Diaz-Fernandez, M. V.; Torices, L.; Nunes-Xavier, C. E.; Pulido, R.; Arango-Lasprilla, J. C.; and Cortes, J. M.\n\n\n \n\n\n\n Journal of Clinical Medicine, 9(4): 990. April 2020.\n \n\n\n\n
\n\n\n\n \n \n $\"Brain$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{de_las_heras_brain_2020,\n\ttitle = {Brain {Circuit} {Alterations} and {Cognitive} {Disability} in {Late}-{Onset} {Cobalamin} {D} {Disorder}},\n\tvolume = {9},\n\tcopyright = {https://creativecommons.org/licenses/by/4.0/},\n\tissn = {2077-0383},\n\turl = {https://www.mdpi.com/2077-0383/9/4/990},\n\tdoi = {10.3390/jcm9040990},\n\tabstract = {Neuroimaging studies describing brain circuits’ alterations in cobalamin (vitamin B12)-deficient patients are limited and have not been carried out in patients with inborn errors of cobalamin metabolism. The objective of this study was to assess brain functionality and brain circuit alterations in a patient with an ultra-rare inborn error of cobalamin metabolism, methylmalonic aciduria, and homocystinuria due to cobalamin D disease, as compared with his twin sister as a healthy control (HC). We acquired magnetic resonance imaging (including structural, functional, and diffusion images) to calculate brain circuit abnormalities and combined these results with the scores after a comprehensive neuropsychological evaluation. As compared with HC, the patient had severe patterns of damage, such as a 254\\% increment of ventricular volume, pronounced subcortical and cortical atrophies (mainly at striatum, cingulate cortex, and precuneus), and connectivity alterations at fronto-striato-thalamic circuit, cerebellum, and corpus callosum. In agreement with brain circuit alterations, cognitive deficits existed in attention, executive function, inhibitory control, and mental flexibility. This is the first study that provides the clinical, genetic, neuroanatomical, neuropsychological, and psychosocial characterization of a patient with the cobalamin D disorder, showing functional alterations in central nervous system motor tracts, thalamus, cerebellum, and basal ganglia, that, as far as we know, have not been reported yet in vitamin B12-related disorders.},\n\tlanguage = {en},\n\tnumber = {4},\n\turldate = {2024-04-15},\n\tjournal = {Journal of Clinical Medicine},\n\tauthor = {De Las Heras, Javier and Diez, Ibai and Jimenez-Marin, Antonio and Cabrera, Alberto and Ramos-Usuga, Daniela and Diaz-Fernandez, Marta Venecia and Torices, Leire and Nunes-Xavier, Caroline E. and Pulido, Rafael and Arango-Lasprilla, Juan Carlos and Cortes, Jesus M.},\n\tmonth = apr,\n\tyear = {2020},\n\tpages = {990},\n}\n\n\n\n\n\n\n\n\n\n\n\n

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\n \n\n \n \n \n \n \n \n Brain connectivity and cognitive functioning in individuals six months after multiorgan failure.\n \n \n \n \n\n\n \n Jimenez-Marin, A.; Rivera, D.; Boado, V.; Diez, I.; Labayen, F.; Garrido, I.; Ramos-Usuga, D.; Benito-Sánchez, I.; Rasero, J.; Cabrera-Zubizarreta, A.; Gabilondo, I.; Stramaglia, S.; Arango-Lasprilla, J. C.; and Cortes, J. M.\n\n\n \n\n\n\n NeuroImage: Clinical, 25: 102137. 2020.\n \n\n\n\n
\n\n\n\n \n \n $\"Brain$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{jimenez-marin_brain_2020,\n\ttitle = {Brain connectivity and cognitive functioning in individuals six months after multiorgan failure},\n\tvolume = {25},\n\tissn = {22131582},\n\turl = {https://linkinghub.elsevier.com/retrieve/pii/S2213158219304838},\n\tdoi = {10.1016/j.nicl.2019.102137},\n\tlanguage = {en},\n\turldate = {2024-04-15},\n\tjournal = {NeuroImage: Clinical},\n\tauthor = {Jimenez-Marin, Antonio and Rivera, Diego and Boado, Victoria and Diez, Ibai and Labayen, Fermin and Garrido, Irati and Ramos-Usuga, Daniela and Benito-Sánchez, Itziar and Rasero, Javier and Cabrera-Zubizarreta, Alberto and Gabilondo, Iñigo and Stramaglia, Sebastiano and Arango-Lasprilla, Juan Carlos and Cortes, Jesus M.},\n\tyear = {2020},\n\tpages = {102137},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Neurodegeneration trajectory in pediatric and adult/late DM1: A follow‐up MRI study across a decade.\n \n \n \n \n\n\n \n Labayru, G.; Jimenez‐Marin, A.; Fernández, E.; Villanua, J.; Zulaica, M.; Cortes, J. M.; Díez, I.; Sepulcre, J.; López De Munain, A.; and Sistiaga, A.\n\n\n \n\n\n\n Annals of Clinical and Translational Neurology, 7(10): 1802–1815. October 2020.\n \n\n\n\n
\n\n\n\n \n \n $\"Neurodegeneration$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{labayru_neurodegeneration_2020,\n\ttitle = {Neurodegeneration trajectory in pediatric and adult/late {DM1}: {A} follow‐up {MRI} study across a decade},\n\tvolume = {7},\n\tissn = {2328-9503, 2328-9503},\n\tshorttitle = {Neurodegeneration trajectory in pediatric and adult/late {DM1}},\n\turl = {https://onlinelibrary.wiley.com/doi/10.1002/acn3.51163},\n\tdoi = {10.1002/acn3.51163},\n\tabstract = {Abstract\n            \n              Objective\n              To characterize the progression of brain structural abnormalities in adults with pediatric and adult/late onset DM1, as well as to examine the potential predictive markers of such progression.\n            \n            \n              Methods\n              21 DM1 patients (pediatric onset: N = 9; adult/late onset: N = 12) and 18 healthy controls (HC) were assessed longitudinally over 9.17 years through brain MRI. Additionally, patients underwent neuropsychological, genetic, and muscular impairment assessment. Inter‐group comparisons of total and voxel‐level regional brain volume were conducted through Voxel Based Morphometry (VBM); cross‐sectionally and longitudinally, analyzing the associations between brain changes and demographic, clinical, and cognitive outcomes.\n            \n            \n              Results\n              The percentage of GM loss did not significantly differ in any of the groups compared with HC and when assessed independently, adult/late DM1 patients and their HC group suffered a significant loss in WM volume. Regional VBM analyses revealed subcortical GM damage in both DM1 groups, evolving to frontal regions in the pediatric onset patients. Muscular impairment and the outcomes of certain neuropsychological tests were significantly associated with follow‐up GM damage, while visuoconstruction, attention, and executive function tests showed sensitivity to WM degeneration over time.\n            \n            \n              Interpretation\n              Distinct patterns of brain atrophy and its progression over time in pediatric and adult/late onset DM1 patients are suggested. Results indicate a possible neurodevelopmental origin of the brain abnormalities in DM1, along with the possible existence of an additional neurodegenerative process. Fronto‐subcortical networks appear to be involved in the disease progression at young adulthood in pediatric onset DM1 patients. The involvement of a multimodal integration network in DM1 is discussed.},\n\tlanguage = {en},\n\tnumber = {10},\n\turldate = {2024-04-15},\n\tjournal = {Annals of Clinical and Translational Neurology},\n\tauthor = {Labayru, Garazi and Jimenez‐Marin, Antonio and Fernández, Esther and Villanua, Jorge and Zulaica, Miren and Cortes, Jesus M. and Díez, Ibai and Sepulcre, Jorge and López De Munain, Adolfo and Sistiaga, Andone},\n\tmonth = oct,\n\tyear = {2020},\n\tpages = {1802--1815},\n}\n\n\n\n\n\n\n\n

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\n \n\n \n \n \n \n \n \n Serum markers improve current prediction of metastasis development in early‐stage melanoma patients: a machine learning‐based study.\n \n \n \n \n\n\n \n Mancuso, F.; Lage, S.; Rasero, J.; Díaz‐Ramón, J. L.; Apraiz, A.; Pérez‐Yarza, G.; Ezkurra, P. A.; Penas, C.; Sánchez‐Diez, A.; García‐Vazquez, M. D.; Gardeazabal, J.; Izu, R.; Mujika, K.; Cortés, J.; Asumendi, A.; and Boyano, M. D.\n\n\n \n\n\n\n Molecular Oncology, 14(8): 1705–1718. August 2020.\n \n\n\n\n
\n\n\n\n \n \n $\"Serum$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{mancuso_serum_2020,\n\ttitle = {Serum markers improve current prediction of metastasis development in early‐stage melanoma patients: a machine learning‐based study},\n\tvolume = {14},\n\tissn = {1574-7891, 1878-0261},\n\tshorttitle = {Serum markers improve current prediction of metastasis development in early‐stage melanoma patients},\n\turl = {https://febs.onlinelibrary.wiley.com/doi/10.1002/1878-0261.12732},\n\tdoi = {10.1002/1878-0261.12732},\n\tabstract = {Metastasis development represents an important threat for melanoma patients, even when diagnosed at early stages and upon removal of the primary tumor. In this scenario, determination of prognostic biomarkers would be of great interest. Serum contains information about the general status of the organism and therefore represents a valuable source for biomarkers. Thus, we aimed to define serological biomarkers that could be used along with clinical and histopathological features of the disease to predict metastatic events on the early‐stage population of patients. We previously demonstrated that in stage II melanoma patients, serum levels of dermcidin (DCD) were associated with metastatic progression. Based on the relevance of the immune response on the cancer progression and the recent association of DCD with local and systemic immune response against cancer cells, serum DCD was analyzed in a new cohort of patients along with interleukin 4 (IL‐4), IL‐6, IL‐10, IL‐17A, interferon γ (IFN‐γ), transforming growth factor‐β (TGF‐ β), and granulocyte–macrophage colony‐stimulating factor (GM‐CSF). We initially recruited 448 melanoma patients, 323 of whom were diagnosed as stages I‐II according to AJCC. Levels of selected cytokines were determined by ELISA and Luminex, and obtained data were analyzed employing machine learning and Kaplan–Meier techniques to define an algorithm capable of accurately classifying early‐stage melanoma patients with a high and low risk of developing metastasis. The results show that in early‐stage melanoma patients, serum levels of the cytokines IL‐4, GM‐CSF, and DCD together with the Breslow thickness are those that best predict melanoma metastasis. Moreover, resulting algorithm represents a new tool to discriminate subjects with good prognosis from those with high risk for a future metastasis.},\n\tlanguage = {en},\n\tnumber = {8},\n\turldate = {2024-04-15},\n\tjournal = {Molecular Oncology},\n\tauthor = {Mancuso, Filippo and Lage, Sergio and Rasero, Javier and Díaz‐Ramón, José Luis and Apraiz, Aintzane and Pérez‐Yarza, Gorka and Ezkurra, Pilar Ariadna and Penas, Cristina and Sánchez‐Diez, Ana and García‐Vazquez, María Dolores and Gardeazabal, Jesús and Izu, Rosa and Mujika, Karmele and Cortés, Jesús and Asumendi, Aintzane and Boyano, María Dolores},\n\tmonth = aug,\n\tyear = {2020},\n\tpages = {1705--1718},\n}\n\n\n\n\n\n\n\n\n\n\n\n

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\n \n\n \n \n \n \n \n \n Toward neuroprosthetic real-time communication from in silico to biological neuronal network via patterned optogenetic stimulation.\n \n \n \n \n\n\n \n Mosbacher, Y.; Khoyratee, F.; Goldin, M.; Kanner, S.; Malakai, Y.; Silva, M.; Grassia, F.; Simon, Y. B.; Cortes, J.; Barzilai, A.; Levi, T.; and Bonifazi, P.\n\n\n \n\n\n\n Scientific Reports, 10(1): 7512. May 2020.\n \n\n\n\n
\n\n\n\n \n \n $\"Toward$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{mosbacher_toward_2020,\n\ttitle = {Toward neuroprosthetic real-time communication from in silico to biological neuronal network via patterned optogenetic stimulation},\n\tvolume = {10},\n\tissn = {2045-2322},\n\turl = {https://www.nature.com/articles/s41598-020-63934-4},\n\tdoi = {10.1038/s41598-020-63934-4},\n\tabstract = {Abstract\n            \n              Restoration of the communication between brain circuitry is a crucial step in the recovery of brain damage induced by traumatic injuries or neurological insults. In this work we present a study of real-time unidirectional communication between a spiking neuronal network (SNN) implemented on digital platform and an\n              in-vitro\n              biological neuronal network (BNN), generating similar spontaneous patterns of activity both spatial and temporal. The communication between the networks was established using patterned optogenetic stimulation via a modified digital light projector (DLP) receiving real-time input dictated by the spiking neurons’ state. Each stimulation consisted of a binary image composed of 8 × 8 squares, representing the state of 64 excitatory neurons. The spontaneous and evoked activity of the biological neuronal network was recorded using a multi-electrode array in conjunction with calcium imaging. The image was projected in a sub-portion of the cultured network covered by a subset of the all electrodes. The unidirectional information transmission (SNN to BNN) is estimated using the similarity matrix of the input stimuli and output firing. Information transmission was studied in relation to the distribution of stimulus frequency and stimulus intensity, both regulated by the spontaneous dynamics of the SNN, and to the entrainment of the biological networks. We demonstrate that high information transfer from SNN to BNN is possible and identify a set of conditions under which such transfer can occur, namely when the spiking network synchronizations drive the biological synchronizations (entrainment) and in a linear regime response to the stimuli. This research provides further evidence of possible application of miniaturized SNN in future neuro-prosthetic devices for local replacement of injured micro-circuitries capable to communicate within larger brain networks.},\n\tlanguage = {en},\n\tnumber = {1},\n\turldate = {2024-04-15},\n\tjournal = {Scientific Reports},\n\tauthor = {Mosbacher, Yossi and Khoyratee, Farad and Goldin, Miri and Kanner, Sivan and Malakai, Yenehaetra and Silva, Moises and Grassia, Filippo and Simon, Yoav Ben and Cortes, Jesus and Barzilai, Ari and Levi, Timothée and Bonifazi, Paolo},\n\tmonth = may,\n\tyear = {2020},\n\tpages = {7512},\n}\n\n\n\n\n\n\n\n

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\n \n\n \n \n \n \n \n \n BRAF V600E mutational load as a prognosis biomarker in malignant melanoma.\n \n \n \n \n\n\n \n Sevilla, A.; Morales, M. C.; Ezkurra, P. A.; Rasero, J.; Velasco, V.; Cancho-Galan, G.; Sánchez-Diez, A.; Mujika, K.; Penas, C.; Smith, I.; Asumendi, A.; Cortés, J. M.; Boyano, M. D.; and Alonso, S.\n\n\n \n\n\n\n PLOS ONE, 15(3): e0230136. March 2020.\n \n\n\n\n
\n\n\n\n \n \n $\"BRAF$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{sevilla_braf_2020,\n\ttitle = {{BRAF} {V600E} mutational load as a prognosis biomarker in malignant melanoma},\n\tvolume = {15},\n\tissn = {1932-6203},\n\turl = {https://dx.plos.org/10.1371/journal.pone.0230136},\n\tdoi = {10.1371/journal.pone.0230136},\n\tlanguage = {en},\n\tnumber = {3},\n\turldate = {2024-04-15},\n\tjournal = {PLOS ONE},\n\tauthor = {Sevilla, Arrate and Morales, M. Celia and Ezkurra, Pilar A. and Rasero, Javier and Velasco, Verónica and Cancho-Galan, Goikoane and Sánchez-Diez, Ana and Mujika, Karmele and Penas, Cristina and Smith, Isabel and Asumendi, Aintzane and Cortés, Jesús M. and Boyano, Maria Dolores and Alonso, Santos},\n\teditor = {Chen, Suzie},\n\tmonth = mar,\n\tyear = {2020},\n\tpages = {e0230136},\n}\n\n\n\n\n\n\n\n

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\n \n 2019\n \n \n (9)\n \n \n

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\n \n\n \n \n \n \n \n \n The nucleus does not significantly affect the migratory trajectories of amoeba in two-dimensional environments.\n \n \n \n \n\n\n \n De La Fuente, I. M.; Bringas, C.; Malaina, I.; Regner, B.; Pérez-Samartín, A.; Boyano, M. D.; Fedetz, M.; López, J. I.; Pérez-Yarza, G.; Cortes, J. M.; and Sejnowski, T.\n\n\n \n\n\n\n Scientific Reports, 9(1): 16369. November 2019.\n \n\n\n\n
\n\n\n\n \n \n $\"The$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{de_la_fuente_nucleus_2019,\n\ttitle = {The nucleus does not significantly affect the migratory trajectories of amoeba in two-dimensional environments},\n\tvolume = {9},\n\tissn = {2045-2322},\n\turl = {https://www.nature.com/articles/s41598-019-52716-2},\n\tdoi = {10.1038/s41598-019-52716-2},\n\tabstract = {Abstract\n            \n              For a wide range of cells, from bacteria to mammals, locomotion movements are a crucial systemic behavior for cellular life. Despite its importance in a plethora of fundamental physiological processes and human pathologies, how unicellular organisms efficiently regulate their locomotion system is an unresolved question. Here, to understand the dynamic characteristics of the locomotion movements and to quantitatively study the role of the nucleus in the migration of\n              Amoeba proteus\n              we have analyzed the movement trajectories of enucleated and non-enucleated amoebas on flat two-dimensional (2D) surfaces using advanced non-linear physical-mathematical tools and computational methods. Our analysis shows that both non-enucleated and enucleated amoebas display the same kind of dynamic migration structure characterized by highly organized data sequences, super-diffusion, non-trivial long-range positive correlations, persistent dynamics with trend-reinforcing behavior, and move-step fluctuations with scale invariant properties. Our results suggest that the presence of the nucleus does not significantly affect the locomotion of amoeba in 2D environments.},\n\tlanguage = {en},\n\tnumber = {1},\n\turldate = {2024-04-15},\n\tjournal = {Scientific Reports},\n\tauthor = {De La Fuente, Ildefonso M. and Bringas, Carlos and Malaina, Iker and Regner, Benjamin and Pérez-Samartín, Alberto and Boyano, María Dolores and Fedetz, María and López, José I. and Pérez-Yarza, Gorka and Cortes, Jesus M. and Sejnowski, Terrence},\n\tmonth = nov,\n\tyear = {2019},\n\tpages = {16369},\n}\n\n\n\n\n\n\n\n\n\n\n\n

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\n \n\n \n \n \n \n \n \n Myocardial MIBG scintigraphy in genetic Parkinson’s disease as a model for Lewy body disorders.\n \n \n \n \n\n\n \n Gabilondo, I.; Llorens, V.; Rodriguez, T.; Fernández, M.; Concha, T. P.; Acera, M.; Tijero, B.; Murueta-Goyena, A.; Del Pino, R.; Cortés, J.; and Gómez-Esteban, J. C.\n\n\n \n\n\n\n European Journal of Nuclear Medicine and Molecular Imaging, 46(2): 376–384. February 2019.\n \n\n\n\n
\n\n\n\n \n \n $\"Myocardial$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{gabilondo_myocardial_2019,\n\ttitle = {Myocardial {MIBG} scintigraphy in genetic {Parkinson}’s disease as a model for {Lewy} body disorders},\n\tvolume = {46},\n\tissn = {1619-7070, 1619-7089},\n\turl = {http://link.springer.com/10.1007/s00259-018-4183-0},\n\tdoi = {10.1007/s00259-018-4183-0},\n\tlanguage = {en},\n\tnumber = {2},\n\turldate = {2024-04-15},\n\tjournal = {European Journal of Nuclear Medicine and Molecular Imaging},\n\tauthor = {Gabilondo, Iñigo and Llorens, Verónica and Rodriguez, Trinidad and Fernández, Manuel and Concha, Tomas Pérez and Acera, Marian and Tijero, Beatriz and Murueta-Goyena, Ane and Del Pino, Rocío and Cortés, Jesús and Gómez-Esteban, Juan Carlos},\n\tmonth = feb,\n\tyear = {2019},\n\tpages = {376--384},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Metastable Resting State Brain Dynamics.\n \n \n \n \n\n\n \n Beim Graben, P.; Jimenez-Marin, A.; Diez, I.; Cortes, J. M.; Desroches, M.; and Rodrigues, S.\n\n\n \n\n\n\n Frontiers in Computational Neuroscience, 13: 62. September 2019.\n \n\n\n\n
\n\n\n\n \n \n $\"Metastable$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{beim_graben_metastable_2019,\n\ttitle = {Metastable {Resting} {State} {Brain} {Dynamics}},\n\tvolume = {13},\n\tissn = {1662-5188},\n\turl = {https://www.frontiersin.org/article/10.3389/fncom.2019.00062/full},\n\tdoi = {10.3389/fncom.2019.00062},\n\turldate = {2024-04-15},\n\tjournal = {Frontiers in Computational Neuroscience},\n\tauthor = {Beim Graben, Peter and Jimenez-Marin, Antonio and Diez, Ibai and Cortes, Jesus M. and Desroches, Mathieu and Rodrigues, Serafim},\n\tmonth = sep,\n\tyear = {2019},\n\tpages = {62},\n}\n\n\n\n\n\n\n\n\n\n\n\n

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\n \n\n \n \n \n \n \n \n Regional brain atrophy in gray and white matter is associated with cognitive impairment in Myotonic Dystrophy type 1.\n \n \n \n \n\n\n \n Labayru, G.; Diez, I.; Sepulcre, J.; Fernández, E.; Zulaica, M.; Cortés, J. M.; López De Munain, A.; and Sistiaga, A.\n\n\n \n\n\n\n NeuroImage: Clinical, 24: 102078. 2019.\n \n\n\n\n
\n\n\n\n \n \n $\"Regional$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{labayru_regional_2019,\n\ttitle = {Regional brain atrophy in gray and white matter is associated with cognitive impairment in {Myotonic} {Dystrophy} type 1},\n\tvolume = {24},\n\tissn = {22131582},\n\turl = {https://linkinghub.elsevier.com/retrieve/pii/S2213158219304255},\n\tdoi = {10.1016/j.nicl.2019.102078},\n\tlanguage = {en},\n\turldate = {2024-04-15},\n\tjournal = {NeuroImage: Clinical},\n\tauthor = {Labayru, Garazi and Diez, Ibai and Sepulcre, Jorge and Fernández, Esther and Zulaica, Miren and Cortés, Jesús M. and López De Munain, Adolfo and Sistiaga, Andone},\n\tyear = {2019},\n\tpages = {102078},\n}\n\n\n\n\n\n\n\n

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\n \n\n \n \n \n \n \n \n Parafoveal thinning of inner retina is associated with visual dysfunction in Lewy body diseases.\n \n \n \n \n\n\n \n Murueta‐Goyena, A.; Del Pino, R.; Reyero, P.; Galdós, M.; Arana, B.; Lucas‐Jiménez, O.; Acera, M.; Tijero, B.; Ibarretxe‐Bilbao, N.; Ojeda, N.; Peña, J.; Cortés, J.; Gómez‐Esteban, J. C.; and Gabilondo, I.\n\n\n \n\n\n\n Movement Disorders, 34(9): 1315–1324. September 2019.\n \n\n\n\n
\n\n\n\n \n \n $\"Parafoveal$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{muruetagoyena_parafoveal_2019,\n\ttitle = {Parafoveal thinning of inner retina is associated with visual dysfunction in {Lewy} body diseases},\n\tvolume = {34},\n\tissn = {0885-3185, 1531-8257},\n\turl = {https://movementdisorders.onlinelibrary.wiley.com/doi/10.1002/mds.27728},\n\tdoi = {10.1002/mds.27728},\n\tabstract = {Abstract\n            \n              Background\n              Retinal optical coherence tomography findings in Lewy body diseases and their implications for visual outcomes remain controversial. We investigated whether region‐specific thickness analysis of retinal layers could improve the detection of macular atrophy and unravel its association with visual disability in Parkinson's disease.\n            \n            \n              Methods\n              \n                Patients with idiopathic Parkinson's disease (n = 63), dementia with Lewy bodies (n = 8), and E46K mutation carriers in the α‐synuclein gene (E46K‐\n                SNCA\n                ) (n = 4) and 34 controls underwent Spectralis optical coherence tomography macular scans and a comprehensive battery of visual function and cognition tests. We computed mean retinal layer thicknesses of both eyes within 1‐, 2‐, 3‐, and 6‐mm diameter macular discs and in concentric parafoveal (1‐ to 2‐mm, 2‐ to 3‐mm, 1‐ to 3‐mm) and perifoveal (3‐ to 6‐mm) rings. Group differences in imaging parameters and their relationship with visual outcomes were analyzed. A multivariate logistic model was developed to predict visual impairment from optical coherence tomography measurements in Parkinson's disease, and cutoff values were determined with receiver operating characteristic analysis.\n              \n            \n            \n              Results\n              \n                When compared with controls, patients with dementia with Lewy bodies had significant thinning of the ganglion cell–inner plexiform layer complex within the central 3‐mm disc mainly because of differences in 1‐ to 3‐mm parafoveal thickness. This parameter was strongly correlated in patients, but not in controls, with low contrast visual acuity and visual cognition outcomes (\n                P\n                {\\textless} .05, False Discovery Rate), achieving 88\\% of accuracy in predicting visual impairment in Parkinson's disease.\n              \n            \n            \n              Conclusion\n              \n                Our findings support that parafoveal thinning of ganglion cell–inner plexiform complex is a sensitive and clinically relevant imaging biomarker for Lewy body diseases, specifically for Parkinson's disease. © 2019 The Authors.\n                Movement Disorders\n                published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.},\n\tlanguage = {en},\n\tnumber = {9},\n\turldate = {2024-04-15},\n\tjournal = {Movement Disorders},\n\tauthor = {Murueta‐Goyena, Ane and Del Pino, Rocío and Reyero, Paula and Galdós, Marta and Arana, Begoña and Lucas‐Jiménez, Olaia and Acera, Marian and Tijero, Beatriz and Ibarretxe‐Bilbao, Naroa and Ojeda, Natalia and Peña, Javier and Cortés, Jesús and Gómez‐Esteban, Juan Carlos and Gabilondo, Iñigo},\n\tmonth = sep,\n\tyear = {2019},\n\tpages = {1315--1324},\n}\n\n\n\n\n\n\n\n

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\n Abstract Background Retinal optical coherence tomography findings in Lewy body diseases and their implications for visual outcomes remain controversial. We investigated whether region‐specific thickness analysis of retinal layers could improve the detection of macular atrophy and unravel its association with visual disability in Parkinson's disease. Methods Patients with idiopathic Parkinson's disease (n = 63), dementia with Lewy bodies (n = 8), and E46K mutation carriers in the α‐synuclein gene (E46K‐ SNCA ) (n = 4) and 34 controls underwent Spectralis optical coherence tomography macular scans and a comprehensive battery of visual function and cognition tests. We computed mean retinal layer thicknesses of both eyes within 1‐, 2‐, 3‐, and 6‐mm diameter macular discs and in concentric parafoveal (1‐ to 2‐mm, 2‐ to 3‐mm, 1‐ to 3‐mm) and perifoveal (3‐ to 6‐mm) rings. Group differences in imaging parameters and their relationship with visual outcomes were analyzed. A multivariate logistic model was developed to predict visual impairment from optical coherence tomography measurements in Parkinson's disease, and cutoff values were determined with receiver operating characteristic analysis. Results When compared with controls, patients with dementia with Lewy bodies had significant thinning of the ganglion cell–inner plexiform layer complex within the central 3‐mm disc mainly because of differences in 1‐ to 3‐mm parafoveal thickness. This parameter was strongly correlated in patients, but not in controls, with low contrast visual acuity and visual cognition outcomes ( P \\textless .05, False Discovery Rate), achieving 88% of accuracy in predicting visual impairment in Parkinson's disease. Conclusion Our findings support that parafoveal thinning of ganglion cell–inner plexiform complex is a sensitive and clinically relevant imaging biomarker for Lewy body diseases, specifically for Parkinson's disease. © 2019 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.\n

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\n \n\n \n \n \n \n \n \n Protein tyrosine phosphatase PTPN1 modulates cell growth and associates with poor outcome in human neuroblastoma.\n \n \n \n \n\n\n \n Nunes-Xavier, C. E.; Aurtenetxe, O.; Zaldumbide, L.; López-Almaraz, R.; Erramuzpe, A.; Cortés, J. M.; López, J. I.; and Pulido, R.\n\n\n \n\n\n\n Diagnostic Pathology, 14(1): 134. December 2019.\n \n\n\n\n
\n\n\n\n \n \n $\"Protein$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{nunes-xavier_protein_2019,\n\ttitle = {Protein tyrosine phosphatase {PTPN1} modulates cell growth and associates with poor outcome in human neuroblastoma},\n\tvolume = {14},\n\tissn = {1746-1596},\n\turl = {https://diagnosticpathology.biomedcentral.com/articles/10.1186/s13000-019-0919-9},\n\tdoi = {10.1186/s13000-019-0919-9},\n\tabstract = {Abstract\n            \n              Background\n              Protein tyrosine phosphatases (PTPs) regulate neuronal differentiation and survival, but their expression patterns and functions in human neuroblastoma (NB) are scarcely known. Here, we have investigated the function and expression of the non-receptor PTPN1 on human NB cell lines and human NB tumor samples.\n            \n            \n              Material/methods\n              NB tumor samples from 44 patients were analysed by immunohistochemistry using specific antibodies against PTPN1, PTPRH, PTPRZ1, and PTEN. PTPN1 knock-down, cell proliferation and tyrosine phosphorylation analyses, and RT-qPCR mRNA expression was assessed on SH-SY5Y, SMS-KCNR, and IMR-32 human NB cell lines.\n            \n            \n              Results\n              Knock-down of PTPN1 in SH-SY5Y NB cells resulted in increased tyrosine phosphorylation and cell proliferation. Retinoic acid-mediated differentiation of NB cell lines did not affect PTPN1 mRNA expression, as compared with other PTPs. Importantly, PTPN1 displayed high expression on NB tumors in association with metastasis and poor prognosis.\n            \n            \n              Conclusions\n              Our results identify PTPN1 as a candidate regulator of NB cell growth and a potential NB prognostic biomarker.},\n\tlanguage = {en},\n\tnumber = {1},\n\turldate = {2024-04-15},\n\tjournal = {Diagnostic Pathology},\n\tauthor = {Nunes-Xavier, Caroline E. and Aurtenetxe, Olaia and Zaldumbide, Laura and López-Almaraz, Ricardo and Erramuzpe, Asier and Cortés, Jesús M. and López, José I. and Pulido, Rafael},\n\tmonth = dec,\n\tyear = {2019},\n\tpages = {134},\n}\n\n\n\n\n\n\n\n

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\n \n\n \n \n \n \n \n \n Connectome sorting by consensus clustering increases separability in group neuroimaging studies.\n \n \n \n \n\n\n \n Rasero, J.; Diez, I.; Cortes, J. M.; Marinazzo, D.; and Stramaglia, S.\n\n\n \n\n\n\n Network Neuroscience, 3(2): 325–343. January 2019.\n \n\n\n\n
\n\n\n\n \n \n $\"Connectome$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{rasero_connectome_2019,\n\ttitle = {Connectome sorting by consensus clustering increases separability in group neuroimaging studies},\n\tvolume = {3},\n\tissn = {2472-1751},\n\turl = {https://direct.mit.edu/netn/article/3/2/325-343/2215},\n\tdoi = {10.1162/netn_a_00074},\n\tabstract = {A fundamental challenge in preprocessing pipelines for neuroimaging datasets is to increase the signal-to-noise ratio for subsequent analyses. In the same line, we suggest here that the application of the consensus clustering approach to brain connectivity matrices can be a valid additional step for connectome processing to find subgroups of subjects with reduced intragroup variability and therefore increasing the separability of the distinct subgroups when connectomes are used as a biomarker. Moreover, by partitioning the data with consensus clustering before any group comparison (for instance, between a healthy population vs. a pathological one), we demonstrate that unique regions within each cluster arise and bring new information that could be relevant from a clinical point of view.},\n\tlanguage = {en},\n\tnumber = {2},\n\turldate = {2024-04-15},\n\tjournal = {Network Neuroscience},\n\tauthor = {Rasero, Javier and Diez, Ibai and Cortes, Jesus M. and Marinazzo, Daniele and Stramaglia, Sebastiano},\n\tmonth = jan,\n\tyear = {2019},\n\tpages = {325--343},\n}\n\n\n\n\n\n\n\n

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\n \n\n \n \n \n \n \n \n PTEN Activity Defines an Axis for Plasticity at Cortico-Amygdala Synapses and Influences Social Behavior.\n \n \n \n \n\n\n \n Sánchez-Puelles, C.; Calleja-Felipe, M.; Ouro, A.; Bougamra, G.; Arroyo, A.; Diez, I.; Erramuzpe, A.; Cortés, J.; Martínez-Hernández, J.; Luján, R.; Navarrete, M.; Venero, C.; Chan, A.; Morales, M.; Esteban, J. A; and Knafo, S.\n\n\n \n\n\n\n Cerebral Cortex,bhz103. June 2019.\n \n\n\n\n
\n\n\n\n \n \n $\"PTEN$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{sanchez-puelles_pten_2019,\n\ttitle = {{PTEN} {Activity} {Defines} an {Axis} for {Plasticity} at {Cortico}-{Amygdala} {Synapses} and {Influences} {Social} {Behavior}},\n\tcopyright = {https://academic.oup.com/journals/pages/open\\_access/funder\\_policies/chorus/standard\\_publication\\_model},\n\tissn = {1047-3211, 1460-2199},\n\turl = {https://academic.oup.com/cercor/advance-article/doi/10.1093/cercor/bhz103/5521615},\n\tdoi = {10.1093/cercor/bhz103},\n\tabstract = {Abstract\n            Phosphatase and tensin homolog on chromosome 10 (PTEN) is a tumor suppressor and autism-associated gene that exerts an important influence over neuronal structure and function during development. In addition, it participates in synaptic plasticity processes in adulthood. As an attempt to assess synaptic and developmental mechanisms by which PTEN can modulate cognitive function, we studied the consequences of 2 different genetic manipulations in mice: presence of additional genomic copies of the Pten gene (Ptentg) and knock-in of a truncated Pten gene lacking its PDZ motif (Pten-ΔPDZ), which is required for interaction with synaptic proteins. Ptentg mice exhibit substantial microcephaly, structural hypoconnectivity, enhanced synaptic depression at cortico-amygdala synapses, reduced anxiety, and intensified social interactions. In contrast, Pten-ΔPDZ mice have a much more restricted phenotype, with normal synaptic connectivity, but impaired synaptic depression at cortico-amygdala synapses and virtually abolished social interactions. These results suggest that synaptic actions of PTEN in the amygdala contribute to specific behavioral traits, such as sociability. Also, PTEN appears to function as a bidirectional rheostat in the amygdala: reduction in PTEN activity at synapses is associated with less sociability, whereas enhanced PTEN activity accompanies hypersocial behavior.},\n\tlanguage = {en},\n\turldate = {2024-04-15},\n\tjournal = {Cerebral Cortex},\n\tauthor = {Sánchez-Puelles, Cristina and Calleja-Felipe, María and Ouro, Alberto and Bougamra, Ghassen and Arroyo, Ana and Diez, Ibai and Erramuzpe, Asier and Cortés, Jesús and Martínez-Hernández, José and Luján, Rafael and Navarrete, Marta and Venero, César and Chan, Andrew and Morales, Miguel and Esteban, José A and Knafo, Shira},\n\tmonth = jun,\n\tyear = {2019},\n\tpages = {bhz103},\n}\n\n\n\n\n\n\n\n

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\n \n\n \n \n \n \n \n \n Corrigendum to: -PTEN activity defines an axis for plasticity at cortico-amygdala synapses and influences social behavior.\n \n \n \n \n\n\n \n Sánchez-Puelles, C.; Calleja-Felipe, M.; Ouro, A.; Bougamra, G.; Arroyo, A.; Diez, I.; Erramuzpe, A.; Cortés, J.; Martínez-Hernández, J.; Luján, R.; Navarrete, M.; Venero, C.; Chan, A.; Morales, M.; Esteban, J. A; and Knafo, S.\n\n\n \n\n\n\n Cerebral Cortex,bhz232. September 2019.\n \n\n\n\n
\n\n\n\n \n \n $\"Corrigendum$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{sanchez-puelles_corrigendum_2019,\n\ttitle = {Corrigendum to: -{PTEN} activity defines an axis for plasticity at cortico-amygdala synapses and influences social behavior},\n\tcopyright = {https://academic.oup.com/journals/pages/open\\_access/funder\\_policies/chorus/standard\\_publication\\_model},\n\tissn = {1047-3211, 1460-2199},\n\tshorttitle = {Corrigendum to},\n\turl = {https://academic.oup.com/cercor/advance-article/doi/10.1093/cercor/bhz232/5574911},\n\tdoi = {10.1093/cercor/bhz232},\n\tlanguage = {en},\n\turldate = {2024-04-15},\n\tjournal = {Cerebral Cortex},\n\tauthor = {Sánchez-Puelles, Cristina and Calleja-Felipe, María and Ouro, Alberto and Bougamra, Ghassen and Arroyo, Ana and Diez, Ibai and Erramuzpe, Asier and Cortés, Jesús and Martínez-Hernández, José and Luján, Rafael and Navarrete, Marta and Venero, César and Chan, Andrew and Morales, Miguel and Esteban, José A and Knafo, Shira},\n\tmonth = sep,\n\tyear = {2019},\n\tpages = {bhz232},\n}\n\n\n\n\n\n\n\n

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\n \n\n \n \n \n \n \n \n Structure–function multi‐scale connectomics reveals a major role of the fronto‐striato‐thalamic circuit in brain aging.\n \n \n \n \n\n\n \n Bonifazi, P.; Erramuzpe, A.; Diez, I.; Gabilondo, I.; Boisgontier, M. P.; Pauwels, L.; Stramaglia, S.; Swinnen, S. P.; and Cortes, J. M.\n\n\n \n\n\n\n Human Brain Mapping, 39(12): 4663–4677. December 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Structure–function$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{bonifazi_structurefunction_2018,\n\ttitle = {Structure–function multi‐scale connectomics reveals a major role of the fronto‐striato‐thalamic circuit in brain aging},\n\tvolume = {39},\n\tissn = {1065-9471, 1097-0193},\n\turl = {https://onlinelibrary.wiley.com/doi/10.1002/hbm.24312},\n\tdoi = {10.1002/hbm.24312},\n\tabstract = {Abstract\n            \n              Physiological aging affects brain structure and function impacting morphology, connectivity, and performance. However, whether some brain connectivity metrics might reflect the age of an individual is still unclear. Here, we collected brain images from healthy participants (\n              N\n               = 155) ranging from 10 to 80 years to build functional (resting state) and structural (tractography) connectivity matrices, both data sets combined to obtain different connectivity features. We then calculated the brain connectome age—an age estimator resulting from a multi‐scale methodology applied to the structure–function connectome, and compared it to the chronological age (ChA). Our results were twofold. First, we found that aging widely affects the connectivity of multiple structures, such as anterior cingulate and medial prefrontal cortices, basal ganglia, thalamus, insula, cingulum, hippocampus, parahippocampus, occipital cortex, fusiform, precuneus, and temporal pole. Second, we found that the connectivity between basal ganglia and thalamus to frontal areas, also known as the fronto‐striato‐thalamic (FST) circuit, makes the major contribution to age estimation. In conclusion, our results highlight the key role played by the FST circuit in the process of healthy aging. Notably, the same methodology can be generally applied to identify the structural–functional connectivity patterns correlating to other biomarkers than ChA.},\n\tlanguage = {en},\n\tnumber = {12},\n\turldate = {2024-04-15},\n\tjournal = {Human Brain Mapping},\n\tauthor = {Bonifazi, Paolo and Erramuzpe, Asier and Diez, Ibai and Gabilondo, Iñigo and Boisgontier, Matthieu P. and Pauwels, Lisa and Stramaglia, Sebastiano and Swinnen, Stephan P. and Cortes, Jesus M.},\n\tmonth = dec,\n\tyear = {2018},\n\tpages = {4663--4677},\n}\n\n\n\n\n\n\n\n

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\n \n\n \n \n \n \n \n \n Multisite tumor sampling enhances the detection of intratumor heterogeneity at all different temporal stages of tumor evolution.\n \n \n \n \n\n\n \n Erramuzpe, A.; Cortés, J. M.; and López, J. I.\n\n\n \n\n\n\n Virchows Archiv, 472(2): 187–194. February 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Multisite$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{erramuzpe_multisite_2018,\n\ttitle = {Multisite tumor sampling enhances the detection of intratumor heterogeneity at all different temporal stages of tumor evolution},\n\tvolume = {472},\n\tissn = {0945-6317, 1432-2307},\n\turl = {http://link.springer.com/10.1007/s00428-017-2223-y},\n\tdoi = {10.1007/s00428-017-2223-y},\n\tlanguage = {en},\n\tnumber = {2},\n\turldate = {2024-04-15},\n\tjournal = {Virchows Archiv},\n\tauthor = {Erramuzpe, Asier and Cortés, Jesús M. and López, José I.},\n\tmonth = feb,\n\tyear = {2018},\n\tpages = {187--194},\n}\n\n\n\n\n\n\n\n

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\n \n\n \n \n \n \n \n \n Interaction Information Along Lifespan of the Resting Brain Dynamics Reveals a Major Redundant Role of the Default Mode Network.\n \n \n \n \n\n\n \n Camino-Pontes, B.; Diez, I.; Jimenez-Marin, A.; Rasero, J.; Erramuzpe, A.; Bonifazi, P.; Stramaglia, S.; Swinnen, S.; and Cortes, J.\n\n\n \n\n\n\n Entropy, 20(10): 742. September 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Interaction$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{camino-pontes_interaction_2018,\n\ttitle = {Interaction {Information} {Along} {Lifespan} of the {Resting} {Brain} {Dynamics} {Reveals} a {Major} {Redundant} {Role} of the {Default} {Mode} {Network}},\n\tvolume = {20},\n\tcopyright = {https://creativecommons.org/licenses/by/4.0/},\n\tissn = {1099-4300},\n\turl = {http://www.mdpi.com/1099-4300/20/10/742},\n\tdoi = {10.3390/e20100742},\n\tabstract = {Interaction Information (II) generalizes the univariate Shannon entropy to triplets of variables, allowing the detection of redundant (R) or synergetic (S) interactions in dynamical networks. Here, we calculated II from functional magnetic resonance imaging data and asked whether R or S vary across brain regions and along lifespan. Preserved along lifespan, we found high overlapping between the pattern of high R and the default mode network, whereas high values of S were overlapping with different cognitive domains, such as spatial and temporal memory, emotion processing and motor skills. Moreover, we have found a robust balance between R and S among different age intervals, indicating informational compensatory mechanisms in brain networks.},\n\tlanguage = {en},\n\tnumber = {10},\n\turldate = {2024-04-15},\n\tjournal = {Entropy},\n\tauthor = {Camino-Pontes, Borja and Diez, Ibai and Jimenez-Marin, Antonio and Rasero, Javier and Erramuzpe, Asier and Bonifazi, Paolo and Stramaglia, Sebastiano and Swinnen, Stephan and Cortes, Jesus},\n\tmonth = sep,\n\tyear = {2018},\n\tpages = {742},\n}\n\n\n\n\n\n\n\n\n\n\n\n

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\n \n\n \n \n \n \n \n \n DUSP5 expression associates with poor prognosis in human neuroblastoma.\n \n \n \n \n\n\n \n Aurtenetxe, O.; Zaldumbide, L.; Erramuzpe, A.; López, R.; López, J. I.; Cortés, J. M.; Pulido, R.; and Nunes-Xavier, C. E.\n\n\n \n\n\n\n Experimental and Molecular Pathology, 105(3): 272–278. December 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"DUSP5$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{aurtenetxe_dusp5_2018,\n\ttitle = {{DUSP5} expression associates with poor prognosis in human neuroblastoma},\n\tvolume = {105},\n\tissn = {00144800},\n\turl = {https://linkinghub.elsevier.com/retrieve/pii/S0014480018302363},\n\tdoi = {10.1016/j.yexmp.2018.08.008},\n\tlanguage = {en},\n\tnumber = {3},\n\turldate = {2024-04-15},\n\tjournal = {Experimental and Molecular Pathology},\n\tauthor = {Aurtenetxe, Olaia and Zaldumbide, Laura and Erramuzpe, Asier and López, Ricardo and López, José I. and Cortés, Jesús M. and Pulido, Rafael and Nunes-Xavier, Caroline E.},\n\tmonth = dec,\n\tyear = {2018},\n\tpages = {272--278},\n}\n\n\n\n\n\n\n\n

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\n \n\n \n \n \n \n \n \n Potential impact of PD-L1 (SP-142) immunohistochemical heterogeneity in clear cell renal cell carcinoma immunotherapy.\n \n \n \n \n\n\n \n López, J. I.; Pulido, R.; Cortés, J. M.; Angulo, J. C.; and Lawrie, C. H.\n\n\n \n\n\n\n Pathology - Research and Practice, 214(8): 1110–1114. August 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Potential$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{lopez_potential_2018,\n\ttitle = {Potential impact of {PD}-{L1} ({SP}-142) immunohistochemical heterogeneity in clear cell renal cell carcinoma immunotherapy},\n\tvolume = {214},\n\tissn = {03440338},\n\turl = {https://linkinghub.elsevier.com/retrieve/pii/S0344033818305399},\n\tdoi = {10.1016/j.prp.2018.06.003},\n\tlanguage = {en},\n\tnumber = {8},\n\turldate = {2024-04-15},\n\tjournal = {Pathology - Research and Practice},\n\tauthor = {López, José I. and Pulido, Rafael and Cortés, Jesús M. and Angulo, Javier C. and Lawrie, Charles H.},\n\tmonth = aug,\n\tyear = {2018},\n\tpages = {1110--1114},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Predicting functional networks from region connectivity profiles in task-based versus resting-state fMRI data.\n \n \n \n \n\n\n \n Rasero, J.; Aerts, H.; Ontivero Ortega, M.; Cortes, J. M.; Stramaglia, S.; and Marinazzo, D.\n\n\n \n\n\n\n PLOS ONE, 13(11): e0207385. November 2018.\n \n\n\n\n
\n\n\n\n \n \n $\"Predicting$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{rasero_predicting_2018,\n\ttitle = {Predicting functional networks from region connectivity profiles in task-based versus resting-state {fMRI} data},\n\tvolume = {13},\n\tissn = {1932-6203},\n\turl = {https://dx.plos.org/10.1371/journal.pone.0207385},\n\tdoi = {10.1371/journal.pone.0207385},\n\tlanguage = {en},\n\tnumber = {11},\n\turldate = {2024-04-15},\n\tjournal = {PLOS ONE},\n\tauthor = {Rasero, Javier and Aerts, Hannelore and Ontivero Ortega, Marlis and Cortes, Jesus M. and Stramaglia, Sebastiano and Marinazzo, Daniele},\n\teditor = {Gallicchio, Claudio},\n\tmonth = nov,\n\tyear = {2018},\n\tpages = {e0207385},\n}\n\n\n\n\n\n\n\n

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\n \n 2017\n \n \n (10)\n \n \n

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\n \n\n \n \n \n \n \n \n Enhanced prefrontal functional–structural networks to support postural control deficits after traumatic brain injury in a pediatric population.\n \n \n \n \n\n\n \n Diez, I.; Drijkoningen, D.; Stramaglia, S.; Bonifazi, P.; Marinazzo, D.; Gooijers, J.; Swinnen, S. P.; and Cortes, J. M.\n\n\n \n\n\n\n Network Neuroscience, 1(2): 116–142. June 2017.\n \n\n\n\n
\n\n\n\n \n \n $\"Enhanced$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{diez_enhanced_2017,\n\ttitle = {Enhanced prefrontal functional–structural networks to support postural control deficits after traumatic brain injury in a pediatric population},\n\tvolume = {1},\n\tissn = {2472-1751},\n\turl = {https://direct.mit.edu/netn/article/1/2/116-142/5391},\n\tdoi = {10.1162/NETN_a_00007},\n\tabstract = {Traumatic brain injury (TBI) affects structural connectivity, triggering the reorganization of structural–functional circuits in a manner that remains poorly understood. We focus here on brain network reorganization in relation to postural control deficits after TBI. We enrolled young participants who had suffered moderate to severe TBI, comparing them to young, typically developing control participants. TBI patients (but not controls) recruited prefrontal regions to interact with two separated networks: (1) a subcortical network, including parts of the motor network, basal ganglia, cerebellum, hippocampus, amygdala, posterior cingulate gyrus, and precuneus; and (2) a task-positive network, involving regions of the dorsal attention system, together with dorsolateral and ventrolateral prefrontal regions. We also found that the increased prefrontal connectivity in TBI patients was correlated with some postural control indices, such as the amount of body sway, whereby patients with worse balance increased their connectivity in frontal regions more strongly. The increased prefrontal connectivity found in TBI patients may provide the structural scaffolding for stronger cognitive control of certain behavioral functions, consistent with the observations that various motor tasks are performed less automatically following TBI and that more cognitive control is associated with such actions.\n          , \n            Author Summary\n            Using a new hierarchical atlas whose modules are relevant for both structure and function, we found increased structural and functional connectivity in prefrontal regions in TBI patients as compared to controls, in addition to a general pattern of overall decreased connectivity across the TBI brain. Although this increased prefrontal connectivity reflected interactions between brain areas when participants were at rest, the enhanced connectivity was found to be negatively correlated with active behavior such as postural control performance. Thus our findings, obtained when the brain was at rest, potentially reflect how TBI patients orchestrate task-related activations to support behavior in everyday life. In particular, our findings of enhanced connectivity in TBI might help these patients overcome deficits in cerebellar and subcortical connections, in addition to compensating for deficits when interacting with the task-positive network. Hence, it appears that greater cognitive control is exerted over certain actions in order to overcome deficits in their automatic processing.},\n\tlanguage = {en},\n\tnumber = {2},\n\turldate = {2024-04-15},\n\tjournal = {Network Neuroscience},\n\tauthor = {Diez, Ibai and Drijkoningen, David and Stramaglia, Sebastiano and Bonifazi, Paolo and Marinazzo, Daniele and Gooijers, Jolien and Swinnen, Stephan P. and Cortes, Jesus M.},\n\tmonth = jun,\n\tyear = {2017},\n\tpages = {116--142},\n}\n\n\n\n\n\n\n\n

\n

\n\n\n

\n Traumatic brain injury (TBI) affects structural connectivity, triggering the reorganization of structural–functional circuits in a manner that remains poorly understood. We focus here on brain network reorganization in relation to postural control deficits after TBI. We enrolled young participants who had suffered moderate to severe TBI, comparing them to young, typically developing control participants. TBI patients (but not controls) recruited prefrontal regions to interact with two separated networks: (1) a subcortical network, including parts of the motor network, basal ganglia, cerebellum, hippocampus, amygdala, posterior cingulate gyrus, and precuneus; and (2) a task-positive network, involving regions of the dorsal attention system, together with dorsolateral and ventrolateral prefrontal regions. We also found that the increased prefrontal connectivity in TBI patients was correlated with some postural control indices, such as the amount of body sway, whereby patients with worse balance increased their connectivity in frontal regions more strongly. The increased prefrontal connectivity found in TBI patients may provide the structural scaffolding for stronger cognitive control of certain behavioral functions, consistent with the observations that various motor tasks are performed less automatically following TBI and that more cognitive control is associated with such actions. , Author Summary Using a new hierarchical atlas whose modules are relevant for both structure and function, we found increased structural and functional connectivity in prefrontal regions in TBI patients as compared to controls, in addition to a general pattern of overall decreased connectivity across the TBI brain. Although this increased prefrontal connectivity reflected interactions between brain areas when participants were at rest, the enhanced connectivity was found to be negatively correlated with active behavior such as postural control performance. Thus our findings, obtained when the brain was at rest, potentially reflect how TBI patients orchestrate task-related activations to support behavior in everyday life. In particular, our findings of enhanced connectivity in TBI might help these patients overcome deficits in cerebellar and subcortical connections, in addition to compensating for deficits when interacting with the task-positive network. Hence, it appears that greater cognitive control is exerted over certain actions in order to overcome deficits in their automatic processing.\n

\n\n\n

\n \n\n \n \n \n \n \n \n Detection of Intratumor Heterogeneity in Modern Pathology: A Multisite Tumor Sampling Perspective.\n \n \n \n \n\n\n \n Cortés, J. M.; De Petris, G.; and López, J. I.\n\n\n \n\n\n\n Frontiers in Medicine, 4. March 2017.\n \n\n\n\n
\n\n\n\n \n \n $\"Detection$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{cortes_detection_2017,\n\ttitle = {Detection of {Intratumor} {Heterogeneity} in {Modern} {Pathology}: {A} {Multisite} {Tumor} {Sampling} {Perspective}},\n\tvolume = {4},\n\tissn = {2296-858X},\n\tshorttitle = {Detection of {Intratumor} {Heterogeneity} in {Modern} {Pathology}},\n\turl = {http://journal.frontiersin.org/article/10.3389/fmed.2017.00025/full},\n\tdoi = {10.3389/fmed.2017.00025},\n\turldate = {2024-04-15},\n\tjournal = {Frontiers in Medicine},\n\tauthor = {Cortés, Jesús M. and De Petris, Giovanni and López, José I.},\n\tmonth = mar,\n\tyear = {2017},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Patient‐specific computational modeling of cortical spreading depression via diffusion tensor imaging.\n \n \n \n \n\n\n \n Kroos, J. M.; Marinelli, I.; Diez, I.; Cortes, J. M.; Stramaglia, S.; and Gerardo‐Giorda, L.\n\n\n \n\n\n\n International Journal for Numerical Methods in Biomedical Engineering, 33(11): e2874. November 2017.\n \n\n\n\n
\n\n\n\n \n \n $\"Patient‐specific$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{kroos_patientspecific_2017,\n\ttitle = {Patient‐specific computational modeling of cortical spreading depression via diffusion tensor imaging},\n\tvolume = {33},\n\tcopyright = {http://onlinelibrary.wiley.com/termsAndConditions\\#vor},\n\tissn = {2040-7939, 2040-7947},\n\turl = {https://onlinelibrary.wiley.com/doi/10.1002/cnm.2874},\n\tdoi = {10.1002/cnm.2874},\n\tabstract = {Abstract\n            Cortical spreading depression, a depolarization wave originating in the visual cortex and traveling towards the frontal lobe, is commonly accepted as a correlate of migraine visual aura. As of today, little is known about the mechanisms that can trigger or stop such phenomenon. However, the complex and highly individual characteristics of the brain cortex suggest that the geometry might have a significant impact in supporting or contrasting the propagation of cortical spreading depression. Accurate patient‐specific computational models are fundamental to cope with the high variability in cortical geometries among individuals, but also with the conduction anisotropy induced in a given cortex by the complex neuronal organisation in the grey matter. In this paper, we integrate a distributed model for extracellular potassium concentration with patient‐specific diffusivity tensors derived locally from diffusion tensor imaging data.},\n\tlanguage = {en},\n\tnumber = {11},\n\turldate = {2024-04-15},\n\tjournal = {International Journal for Numerical Methods in Biomedical Engineering},\n\tauthor = {Kroos, Julia M. and Marinelli, Isabella and Diez, Ibai and Cortes, Jesus M. and Stramaglia, Sebastiano and Gerardo‐Giorda, Luca},\n\tmonth = nov,\n\tyear = {2017},\n\tpages = {e2874},\n}\n\n\n\n\n\n\n\n\n\n\n\n

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\n \n\n \n \n \n \n \n \n Building Bridges through Science.\n \n \n \n \n\n\n \n Lissek, T.; Adams, M.; Adelman, J.; Ahissar, E.; Akaaboune, M.; Akil, H.; al’Absi , M.; Arain, F.; Arango-Lasprilla, J. C.; Atasoy, D.; Avila, J.; Badawi, A.; Bading, H.; Baig, A. M.; Baleriola, J.; Belmonte, C.; Bertocchi, I.; Betz, H.; Blakemore, C.; Blanke, O.; Boehm-Sturm, P.; Bonhoeffer, T.; Bonifazi, P.; Brose, N.; Campolongo, P.; Celikel, T.; Chang, C. C.; Chang, T.; Citri, A.; Cline, H. T.; Cortes, J. M.; Cullen, K.; Dean, K.; Delgado-Garcia, J. M.; Desroches, M.; Disterhoft, J. F.; Dowling, J. E.; Draguhn, A.; El-Khamisy, S. F.; El Manira, A.; Enam, S. A.; Encinas, J. M.; Erramuzpe, A.; Esteban, J. A.; Fariñas, I.; Fischer, E.; Fukunaga, I.; Gabilondo, I.; Ganten, D.; Gidon, A.; Gomez-Esteban, J. C.; Greengard, P.; Grinevich, V.; Gruart, A.; Guillemin, R.; Hariri, A. R.; Hassan, B.; Häusser, M.; Hayashi, Y.; Hussain, N. K.; Jabbar, A. A.; Jaber, M.; Jahn, R.; Janahi, E. M.; Kabbaj, M.; Kettenmann, H.; Kindt, M.; Knafo, S.; Köhr, G.; Komai, S.; Krugers, H.; Kuhn, B.; Ghazal, N. L.; Larkum, M. E.; London, M.; Lutz, B.; Matute, C.; Martinez-Millan, L.; Maroun, M.; McGaugh, J.; Moustafa, A. A.; Nasim, A.; Nave, K.; Neher, E.; Nikolich, K.; Outeiro, T.; Palmer, L. M.; Penagarikano, O.; Perez-Otano, I.; Pfaff, D. W.; Poucet, B.; Rahman, A.; Ramos-Cabrer, P.; Rashidy-Pour, A.; Roberts, R. J.; Rodrigues, S.; Sanes, J. R.; Schaefer, A. T.; Segal, M.; Segev, I.; Shafqat, S.; Siddiqui, N. A.; Soreq, H.; Soriano-García, E.; Spanagel, R.; Sprengel, R.; Stuart, G.; Südhof, T. C.; Tønnesen, J.; Treviño, M.; Uthman, B. M.; Venter, J. C.; Verkhratsky, A.; Weiss, C.; Wiesel, T. N.; Yaksi, E.; Yizhar, O.; Young, L. J.; Young, P.; Zawia, N. H.; Zugaza, J. L.; and Hasan, M. T.\n\n\n \n\n\n\n Neuron, 96(4): 730–735. November 2017.\n \n\n\n\n
\n\n\n\n \n \n $\"Building$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{lissek_building_2017,\n\ttitle = {Building {Bridges} through {Science}},\n\tvolume = {96},\n\tissn = {08966273},\n\turl = {https://linkinghub.elsevier.com/retrieve/pii/S0896627317308723},\n\tdoi = {10.1016/j.neuron.2017.09.028},\n\tlanguage = {en},\n\tnumber = {4},\n\turldate = {2024-04-15},\n\tjournal = {Neuron},\n\tauthor = {Lissek, Thomas and Adams, Michelle and Adelman, John and Ahissar, Ehud and Akaaboune, Mohammed and Akil, Huda and al’Absi, Mustafa and Arain, Fazal and Arango-Lasprilla, Juan Carlos and Atasoy, Deniz and Avila, Jesus and Badawi, Ashraf and Bading, Hilmar and Baig, Abdul Mannan and Baleriola, Jimena and Belmonte, Carlos and Bertocchi, Ilaria and Betz, Heinrich and Blakemore, Colin and Blanke, Olaf and Boehm-Sturm, Philipp and Bonhoeffer, Tobias and Bonifazi, Paolo and Brose, Nils and Campolongo, Patrizia and Celikel, Tansu and Chang, Cathy C. and Chang, Ta-Yuan and Citri, Ami and Cline, Hollis T. and Cortes, Jesus M. and Cullen, Kathleen and Dean, Kellie and Delgado-Garcia, José M. and Desroches, Mathieu and Disterhoft, John F. and Dowling, John E. and Draguhn, Andreas and El-Khamisy, Sherif F. and El Manira, Abdeljabbar and Enam, S. Ather and Encinas, Juan M. and Erramuzpe, Asier and Esteban, José A. and Fariñas, Isabel and Fischer, Edmond and Fukunaga, Izumi and Gabilondo, Iñigo and Ganten, Detlev and Gidon, Albert and Gomez-Esteban, Juan Carlos and Greengard, Paul and Grinevich, Valery and Gruart, Agnés and Guillemin, Roger and Hariri, Ahmad R. and Hassan, Bassem and Häusser, Michael and Hayashi, Yasunori and Hussain, Natasha K. and Jabbar, Adnan Abdul and Jaber, Mohamed and Jahn, Reinhardt and Janahi, Essam Mohammed and Kabbaj, Mohamed and Kettenmann, Helmut and Kindt, Merel and Knafo, Shira and Köhr, Georg and Komai, Shoji and Krugers, Harm and Kuhn, Bernd and Ghazal, Nouria Lakhdar and Larkum, Matthew E. and London, Mickey and Lutz, Beat and Matute, Carlos and Martinez-Millan, Luis and Maroun, Mouna and McGaugh, James and Moustafa, Ahmed A. and Nasim, Anwar and Nave, Klaus-Armin and Neher, Erwin and Nikolich, Karoly and Outeiro, Tiago and Palmer, Lucy M. and Penagarikano, Olga and Perez-Otano, Isabel and Pfaff, Donald W. and Poucet, Bruno and Rahman, Atta-ur and Ramos-Cabrer, Pedro and Rashidy-Pour, Ali and Roberts, Richard J. and Rodrigues, Serafim and Sanes, Joshua R. and Schaefer, Andreas T. and Segal, Menahem and Segev, Idan and Shafqat, Saad and Siddiqui, Nikhat Ahmed and Soreq, Hermona and Soriano-García, Eduardo and Spanagel, Rainer and Sprengel, Rolf and Stuart, Greg and Südhof, Thomas C. and Tønnesen, Jan and Treviño, Mario and Uthman, Basim M. and Venter, J. Craig and Verkhratsky, Alexei and Weiss, Craig and Wiesel, Torsten N. and Yaksi, Emre and Yizhar, Ofer and Young, Larry J. and Young, Paul and Zawia, Nasser H. and Zugaza, José L. and Hasan, Mazahir T.},\n\tmonth = nov,\n\tyear = {2017},\n\tpages = {730--735},\n}\n\n\n\n\n\n\n\n

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\n \n\n \n \n \n \n \n \n Multisite tumor sampling: a new tumor selection method to enhance intratumor heterogeneity detection.\n \n \n \n \n\n\n \n López, J. I.; and Cortés, J. M.\n\n\n \n\n\n\n Human Pathology, 64: 1–6. June 2017.\n \n\n\n\n
\n\n\n\n \n \n $\"Multisite$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

\n

@article{lopez_multisite_2017,\n\ttitle = {Multisite tumor sampling: a new tumor selection method to enhance intratumor heterogeneity detection},\n\tvolume = {64},\n\tissn = {00468177},\n\tshorttitle = {Multisite tumor sampling},\n\turl = {https://linkinghub.elsevier.com/retrieve/pii/S0046817717300588},\n\tdoi = {10.1016/j.humpath.2017.02.010},\n\tlanguage = {en},\n\turldate = {2024-04-15},\n\tjournal = {Human Pathology},\n\tauthor = {López, José I. and Cortés, Jesús M.},\n\tmonth = jun,\n\tyear = {2017},\n\tpages = {1--6},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n CD34 immunostaining enhances a distinct pattern of intratumor angiogenesis with prognostic implications in clear cell renal cell carcinoma.\n \n \n \n \n\n\n \n López, J. I.; Erramuzpe, A.; Guarch, R.; Cortés, J. M.; Pulido, R.; Llarena, R.; and Angulo, J. C.\n\n\n \n\n\n\n APMIS, 125(2): 128–133. February 2017.\n \n\n\n\n
\n\n\n\n \n \n $\"CD34$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{lopez_cd34_2017,\n\ttitle = {{CD34} immunostaining enhances a distinct pattern of intratumor angiogenesis with prognostic implications in clear cell renal cell carcinoma},\n\tvolume = {125},\n\tissn = {0903-4641, 1600-0463},\n\turl = {https://onlinelibrary.wiley.com/doi/10.1111/apm.12649},\n\tdoi = {10.1111/apm.12649},\n\tabstract = {Clear cell renal cell carcinoma is an aggressive neoplasm related to\n              \n                VHL\n              \n              gene inactivation. The molecular events derived from this initial alteration lead to a permanent intracellular pseudo‐hypoxic status that stimulates vascular proliferation. The resulting increased intratumor angiogenesis is the target of most modern therapies. Although intratumor angiogenesis has received full attention in the last years, few studies have focused on its potential importance from a strict morphological approach. Intratumor angiogenesis has been analyzed in a retrospective series of clear cell renal cell carcinomas (n = 208) with long‐term follow‐up (n = 177). Two different patterns of angiogenesis have been highlighted with\n              CD\n              34 at the front of tumor invasion, termed continuous and discontinuous, respectively. The continuous pattern of angiogenesis showed a complete microvascular network surrounding totally tumor nests. Conversely, the discontinuous pattern displayed an incomplete network around tumor nests. The continuous pattern was associated to shorter 5‐year (p = 0.00064, hazard ratio = 2.8) and 15‐year (p = 0.014, hazard ratio = 1.7) survivals. Cox regression multivariate analysis also showed that the continuous pattern (p = 0.016373) remains a significant variable when considered together with grade (p = 0.001755) and stage (p = 0.000952). These findings support the notion that a continuous\n              CD\n              34\n              +\n              pattern of intratumor angiogenesis may be useful for pathologists in predicting tumor behavior in clear cell renal cell carcinomas.},\n\tlanguage = {en},\n\tnumber = {2},\n\turldate = {2024-04-15},\n\tjournal = {APMIS},\n\tauthor = {López, José I. and Erramuzpe, Asier and Guarch, Rosa and Cortés, Jesús M. and Pulido, Rafael and Llarena, Roberto and Angulo, Javier C.},\n\tmonth = feb,\n\tyear = {2017},\n\tpages = {128--133},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Dynamic properties of calcium-activated chloride currents in Xenopus laevis oocytes.\n \n \n \n \n\n\n \n M. De La Fuente, I.; Malaina, I.; Pérez-Samartín, A.; Boyano, M. D.; Pérez-Yarza, G.; Bringas, C.; Villarroel, Á.; Fedetz, M.; Arellano, R.; Cortes, J. M.; and Martínez, L.\n\n\n \n\n\n\n Scientific Reports, 7(1): 41791. February 2017.\n \n\n\n\n
\n\n\n\n \n \n $\"Dynamic$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{m_de_la_fuente_dynamic_2017,\n\ttitle = {Dynamic properties of calcium-activated chloride currents in {Xenopus} laevis oocytes},\n\tvolume = {7},\n\tissn = {2045-2322},\n\turl = {https://www.nature.com/articles/srep41791},\n\tdoi = {10.1038/srep41791},\n\tabstract = {Abstract\n            \n              Chloride is the most abundant permeable anion in the cell, and numerous studies in the last two decades highlight the great importance and broad physiological role of chloride currents mediated anion transport. They participate in a multiplicity of key processes, as for instance, the regulation of electrical excitability, apoptosis, cell cycle, epithelial secretion and neuronal excitability. In addition, dysfunction of Cl\n              −\n              channels is involved in a variety of human diseases such as epilepsy, osteoporosis and different cancer types. Historically, chloride channels have been of less interest than the cation channels. In fact, there seems to be practically no quantitative studies of the dynamics of chloride currents. Here, for the first time, we have quantitatively studied experimental calcium-activated chloride fluxes belonging to\n              Xenopus laevis\n              oocytes, and the main results show that the experimental Cl\n              −\n              currents present an informational structure characterized by highly organized data sequences, long-term memory properties and inherent “crossover” dynamics in which persistent correlations arise at short time intervals, while anti-persistent behaviors become dominant in long time intervals. Our work sheds some light on the understanding of the informational properties of ion currents, a key element to elucidate the physiological functional coupling with the integrative dynamics of metabolic processes.},\n\tlanguage = {en},\n\tnumber = {1},\n\turldate = {2024-04-15},\n\tjournal = {Scientific Reports},\n\tauthor = {M. De La Fuente, Ildefonso and Malaina, Iker and Pérez-Samartín, Alberto and Boyano, María Dolores and Pérez-Yarza, Gorka and Bringas, Carlos and Villarroel, Álvaro and Fedetz, María and Arellano, Rogelio and Cortes, Jesus M. and Martínez, Luis},\n\tmonth = feb,\n\tyear = {2017},\n\tpages = {41791},\n}\n\n\n\n\n\n\n\n

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\n \n\n \n \n \n \n \n \n Group-Level Progressive Alterations in Brain Connectivity Patterns Revealed by Diffusion-Tensor Brain Networks across Severity Stages in Alzheimer’s Disease.\n \n \n \n \n\n\n \n Rasero, J.; Alonso-Montes, C.; Diez, I.; Olabarrieta-Landa, L.; Remaki, L.; Escudero, I.; Mateos, B.; Bonifazi, P.; Fernandez, M.; Arango-Lasprilla, J. C.; Stramaglia, S.; Cortes, J. M.; and the Alzheimer’s Disease Neuroimaging Initiative\n\n\n \n\n\n\n Frontiers in Aging Neuroscience, 9: 215. July 2017.\n \n\n\n\n
\n\n\n\n \n \n $\"Group-Level$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{rasero_group-level_2017,\n\ttitle = {Group-{Level} {Progressive} {Alterations} in {Brain} {Connectivity} {Patterns} {Revealed} by {Diffusion}-{Tensor} {Brain} {Networks} across {Severity} {Stages} in {Alzheimer}’s {Disease}},\n\tvolume = {9},\n\tissn = {1663-4365},\n\turl = {http://journal.frontiersin.org/article/10.3389/fnagi.2017.00215/full},\n\tdoi = {10.3389/fnagi.2017.00215},\n\turldate = {2024-04-15},\n\tjournal = {Frontiers in Aging Neuroscience},\n\tauthor = {Rasero, Javier and Alonso-Montes, Carmen and Diez, Ibai and Olabarrieta-Landa, Laiene and Remaki, Lakhdar and Escudero, Iñaki and Mateos, Beatriz and Bonifazi, Paolo and Fernandez, Manuel and Arango-Lasprilla, Juan Carlos and Stramaglia, Sebastiano and Cortes, Jesus M. and {the Alzheimer’s Disease Neuroimaging Initiative}},\n\tmonth = jul,\n\tyear = {2017},\n\tpages = {215},\n}\n\n\n\n\n\n\n\n

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\n \n\n \n \n \n \n \n \n Consensus clustering approach to group brain connectivity matrices.\n \n \n \n \n\n\n \n Rasero, J.; Pellicoro, M.; Angelini, L.; Cortes, J. M.; Marinazzo, D.; and Stramaglia, S.\n\n\n \n\n\n\n Network Neuroscience, 1(3): 242–253. October 2017.\n \n\n\n\n
\n\n\n\n \n \n $\"Consensus$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{rasero_consensus_2017,\n\ttitle = {Consensus clustering approach to group brain connectivity matrices},\n\tvolume = {1},\n\tissn = {2472-1751},\n\turl = {https://direct.mit.edu/netn/article/1/3/242-253/2201},\n\tdoi = {10.1162/NETN_a_00017},\n\tabstract = {A novel approach rooted on the notion of consensus clustering, a strategy developed for community detection in complex networks, is proposed to cope with the heterogeneity that characterizes connectivity matrices in health and disease. The method can be summarized as follows: (a) define, for each node, a distance matrix for the set of subjects by comparing the connectivity pattern of that node in all pairs of subjects; (b) cluster the distance matrix for each node; (c) build the consensus network from the corresponding partitions; and (d) extract groups of subjects by finding the communities of the consensus network thus obtained. Different from the previous implementations of consensus clustering, we thus propose to use the consensus strategy to combine the information arising from the connectivity patterns of each node. The proposed approach may be seen either as an exploratory technique or as an unsupervised pretraining step to help the subsequent construction of a supervised classifier. Applications on a toy model and two real datasets show the effectiveness of the proposed methodology, which represents heterogeneity of a set of subjects in terms of a weighted network, the consensus matrix.},\n\tlanguage = {en},\n\tnumber = {3},\n\turldate = {2024-04-15},\n\tjournal = {Network Neuroscience},\n\tauthor = {Rasero, Javier and Pellicoro, Mario and Angelini, Leonardo and Cortes, Jesus M. and Marinazzo, Daniele and Stramaglia, Sebastiano},\n\tmonth = oct,\n\tyear = {2017},\n\tpages = {242--253},\n}\n\n\n\n\n\n\n\n

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\n \n\n \n \n \n \n \n \n Ising model with conserved magnetization on the human connectome: Implications on the relation structure-function in wakefulness and anesthesia.\n \n \n \n \n\n\n \n Stramaglia, S.; Pellicoro, M.; Angelini, L.; Amico, E.; Aerts, H.; Cortés, J. M.; Laureys, S.; and Marinazzo, D.\n\n\n \n\n\n\n Chaos: An Interdisciplinary Journal of Nonlinear Science, 27(4): 047407. April 2017.\n \n\n\n\n
\n\n\n\n \n \n $\"Ising$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{stramaglia_ising_2017,\n\ttitle = {Ising model with conserved magnetization on the human connectome: {Implications} on the relation structure-function in wakefulness and anesthesia},\n\tvolume = {27},\n\tissn = {1054-1500, 1089-7682},\n\tshorttitle = {Ising model with conserved magnetization on the human connectome},\n\turl = {https://pubs.aip.org/cha/article/27/4/047407/322554/Ising-model-with-conserved-magnetization-on-the},\n\tdoi = {10.1063/1.4978999},\n\tabstract = {Dynamical models implemented on the large scale architecture of the human brain may shed light on how a function arises from the underlying structure. This is the case notably for simple abstract models, such as the Ising model. We compare the spin correlations of the Ising model and the empirical functional brain correlations, both at the single link level and at the modular level, and show that their match increases at the modular level in anesthesia, in line with recent results and theories. Moreover, we show that at the peak of the specific heat (the critical state), the spin correlations are minimally shaped by the underlying structural network, explaining how the best match between the structure and function is obtained at the onset of criticality, as previously observed. These findings confirm that brain dynamics under anesthesia shows a departure from criticality and could open the way to novel perspectives when the conserved magnetization is interpreted in terms of a homeostatic principle imposed to neural activity.},\n\tlanguage = {en},\n\tnumber = {4},\n\turldate = {2024-04-15},\n\tjournal = {Chaos: An Interdisciplinary Journal of Nonlinear Science},\n\tauthor = {Stramaglia, S. and Pellicoro, M. and Angelini, L. and Amico, E. and Aerts, H. and Cortés, J. M. and Laureys, S. and Marinazzo, D.},\n\tmonth = apr,\n\tyear = {2017},\n\tpages = {047407},\n}\n\n\n\n\n\n\n\n

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\n \n 2016\n \n \n (10)\n \n \n

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\n \n\n \n \n \n \n \n \n Multi-site tumor sampling (MSTS) improves the performance of histological detection of intratumor heterogeneity in clear cell renal cell carcinoma (CCRCC).\n \n \n \n \n\n\n \n Guarch, R.; Cortés, J. M.; Lawrie, C. H.; and López, J. I.\n\n\n \n\n\n\n F1000Research, 5: 2020. September 2016.\n \n\n\n\n
\n\n\n\n \n \n $\"Multi-site$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{guarch_multi-site_2016,\n\ttitle = {Multi-site tumor sampling ({MSTS}) improves the performance of histological detection of intratumor heterogeneity in clear cell renal cell carcinoma ({CCRCC})},\n\tvolume = {5},\n\tissn = {2046-1402},\n\turl = {https://f1000research.com/articles/5-2020/v2},\n\tdoi = {10.12688/f1000research.9419.2},\n\tabstract = {Current standard-of-care tumor sampling protocols for CCRCC (and other cancers) are not efficient at detecting intratumoural heterogeneity (ITH). We have demonstrated\n              in silico\n              that an alternative protocol, multi-site tumor sampling (MSTS) based upon the divide and conquer (DAC) algorithm, can significantly increase the efficiency of ITH detection without extra costs. Now we test this protocol on routine hematoxylin-eosin (HE) sections in a series of 38 CCRCC cases. MSTS was found to outperform traditional sampling when detecting either high grade (p=0.0136) or granular/eosinophilic cells (p=0.0114). We therefore propose that MSTS should be used in routine clinical practice.},\n\tlanguage = {en},\n\turldate = {2024-04-15},\n\tjournal = {F1000Research},\n\tauthor = {Guarch, Rosa and Cortés, Jesús M. and Lawrie, Charles H. and López, José I.},\n\tmonth = sep,\n\tyear = {2016},\n\tpages = {2020},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Geometry Shapes Propagation: Assessing the Presence and Absence of Cortical Symmetries through a Computational Model of Cortical Spreading Depression.\n \n \n \n \n\n\n \n Kroos, J. M.; Diez, I.; Cortes, J. M.; Stramaglia, S.; and Gerardo-Giorda, L.\n\n\n \n\n\n\n Frontiers in Computational Neuroscience, 10. February 2016.\n \n\n\n\n
\n\n\n\n \n \n $\"Geometry$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{kroos_geometry_2016,\n\ttitle = {Geometry {Shapes} {Propagation}: {Assessing} the {Presence} and {Absence} of {Cortical} {Symmetries} through a {Computational} {Model} of {Cortical} {Spreading} {Depression}},\n\tvolume = {10},\n\tissn = {1662-5188},\n\tshorttitle = {Geometry {Shapes} {Propagation}},\n\turl = {http://journal.frontiersin.org/Article/10.3389/fncom.2016.00006/abstract},\n\tdoi = {10.3389/fncom.2016.00006},\n\turldate = {2024-04-15},\n\tjournal = {Frontiers in Computational Neuroscience},\n\tauthor = {Kroos, Julia M. and Diez, Ibai and Cortes, Jesus M. and Stramaglia, Sebastiano and Gerardo-Giorda, Luca},\n\tmonth = feb,\n\tyear = {2016},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n A divide-and-conquer strategy in tumor sampling enhances detection of intratumor heterogeneity in routine pathology: A modeling approach in clear cell renal cell carcinoma.\n \n \n \n \n\n\n \n Lopez, J. I.; and Cortes, J. M.\n\n\n \n\n\n\n F1000Research, 5: 385. April 2016.\n \n\n\n\n
\n\n\n\n \n \n $\"A$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{lopez_divide-and-conquer_2016,\n\ttitle = {A divide-and-conquer strategy in tumor sampling enhances detection of intratumor heterogeneity in routine pathology: {A} modeling approach in clear cell renal cell carcinoma},\n\tvolume = {5},\n\tissn = {2046-1402},\n\tshorttitle = {A divide-and-conquer strategy in tumor sampling enhances detection of intratumor heterogeneity in routine pathology},\n\turl = {https://f1000research.com/articles/5-385/v2},\n\tdoi = {10.12688/f1000research.8196.2},\n\tabstract = {Intratumor heterogeneity (ITH) is an inherent process in cancer development which follows for most of the cases a branched pattern of evolution, with different cell clones evolving independently in space and time across different areas of the same tumor. The determination of ITH (in both spatial and temporal domains) is nowadays critical to enhance patient treatment and prognosis. Clear cell renal cell carcinoma (CCRCC) provides a good example of ITH. Sometimes the tumor is too big to be totally analyzed for ITH detection and pathologists decide which parts must be sampled for the analysis. For such a purpose, pathologists follow internationally accepted protocols. In light of the latest findings, however, current sampling protocols seem to be insufficient for detecting ITH with significant reliability. The arrival of new targeted therapies, some of them providing promising alternatives to improve patient survival, pushes the pathologist to obtain a truly representative sampling of tumor diversity in routine practice. How large this sampling must be and how this must be performed are unanswered questions so far.  Here we present a very simple method for tumor sampling that enhances ITH detection without increasing costs. This method follows a divide-and-conquer (DAC) strategy, that is, rather than sampling a small number of large-size tumor-pieces as the routine protocol (RP) advises, we suggest sampling many small-size pieces along the tumor. We performed a computational modeling approach to show that the usefulness of the DAC strategy is twofold: first, we show that DAC outperforms RP with similar laboratory costs, and second, DAC is capable of performing similar to total tumor sampling (TTS) but, very remarkably, at a much lower cost. We thus provide new light to push forward a shift in the paradigm about how pathologists should sample tumors for achieving efficient ITH detection.},\n\tlanguage = {en},\n\turldate = {2024-04-15},\n\tjournal = {F1000Research},\n\tauthor = {Lopez, José I. and Cortes, Jesús M.},\n\tmonth = apr,\n\tyear = {2016},\n\tpages = {385},\n}\n\n\n\n\n\n\n\n

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\n \n\n \n \n \n \n \n \n A multi-site cutting device implements efficiently the divide-and-conquer strategy in tumor sampling.\n \n \n \n \n\n\n \n Lopez, J. I.; and Cortes, J. M.\n\n\n \n\n\n\n F1000Research, 5: 1587. July 2016.\n \n\n\n\n
\n\n\n\n \n \n $\"A$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{lopez_multi-site_2016,\n\ttitle = {A multi-site cutting device implements efficiently the divide-and-conquer strategy in tumor sampling},\n\tvolume = {5},\n\tissn = {2046-1402},\n\turl = {https://f1000research.com/articles/5-1587/v2},\n\tdoi = {10.12688/f1000research.9091.2},\n\tabstract = {We recently showed that in order to detect intra-tumor heterogeneity a Divide-and-Conquer (DAC) strategy of tumor sampling outperforms current routine protocols. This paper is a continuation of this work, but here we focus on DAC implementation in the Pathology Laboratory. In particular, we describe a new simple method that makes use of a cutting grid device and is applied to clear cell renal cell carcinomas for DAC implementation. This method assures a thorough sampling of large surgical specimens, facilitates the demonstration of intratumor heterogeneity, and saves time to pathologists in the daily practice. The method involves the following steps: 1. Thin slicing of the tumor (by hand or machine), 2. Application of a cutting grid to the slices (\n              e.g\n              ., a French fry cutter), resulting in multiple tissue cubes with fixed position within the slice, 3. Selection of tissue cubes for analysis, and finally, 4. Inclusion of selected cubes into a cassette for histological processing (with about eight tissue fragments within each cassette). Thus, using our approach in a 10 cm in-diameter-tumor we generate 80 tumor tissue fragments placed in 10 cassettes and, notably, in a tenth of time. Eighty samples obtained across all the regions of the tumor will assure a much higher performance in detecting intratumor heterogeneity, as proved recently with synthetic data.},\n\tlanguage = {en},\n\turldate = {2024-04-15},\n\tjournal = {F1000Research},\n\tauthor = {Lopez, Jose I. and Cortes, Jesus M.},\n\tmonth = jul,\n\tyear = {2016},\n\tpages = {1587},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Fibroblast activation protein predicts prognosis in clear cell renal cell carcinoma.\n \n \n \n \n\n\n \n López, J. I.; Errarte, P.; Erramuzpe, A.; Guarch, R.; Cortés, J. M.; Angulo, J. C.; Pulido, R.; Irazusta, J.; Llarena, R.; and Larrinaga, G.\n\n\n \n\n\n\n Human Pathology, 54: 100–105. August 2016.\n \n\n\n\n
\n\n\n\n \n \n $\"Fibroblast$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{lopez_fibroblast_2016,\n\ttitle = {Fibroblast activation protein predicts prognosis in clear cell renal cell carcinoma},\n\tvolume = {54},\n\tissn = {00468177},\n\turl = {https://linkinghub.elsevier.com/retrieve/pii/S0046817716300247},\n\tdoi = {10.1016/j.humpath.2016.03.009},\n\tlanguage = {en},\n\turldate = {2024-04-15},\n\tjournal = {Human Pathology},\n\tauthor = {López, José I. and Errarte, Peio and Erramuzpe, Asier and Guarch, Rosa and Cortés, Jesús M. and Angulo, Javier C. and Pulido, Rafael and Irazusta, Jon and Llarena, Roberto and Larrinaga, Gorka},\n\tmonth = aug,\n\tyear = {2016},\n\tpages = {100--105},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n One-Tube-Only Standardized Site-Directed Mutagenesis: An Alternative Approach to Generate Amino Acid Substitution Collections.\n \n \n \n \n\n\n \n Mingo, J.; Erramuzpe, A.; Luna, S.; Aurtenetxe, O.; Amo, L.; Diez, I.; Schepens, J. T. G.; Hendriks, W. J. A. J.; Cortés, J. M.; and Pulido, R.\n\n\n \n\n\n\n PLOS ONE, 11(8): e0160972. August 2016.\n \n\n\n\n
\n\n\n\n \n \n $\"One-Tube-Only$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{mingo_one-tube-only_2016,\n\ttitle = {One-{Tube}-{Only} {Standardized} {Site}-{Directed} {Mutagenesis}: {An} {Alternative} {Approach} to {Generate} {Amino} {Acid} {Substitution} {Collections}},\n\tvolume = {11},\n\tissn = {1932-6203},\n\tshorttitle = {One-{Tube}-{Only} {Standardized} {Site}-{Directed} {Mutagenesis}},\n\turl = {https://dx.plos.org/10.1371/journal.pone.0160972},\n\tdoi = {10.1371/journal.pone.0160972},\n\tlanguage = {en},\n\tnumber = {8},\n\turldate = {2024-04-15},\n\tjournal = {PLOS ONE},\n\tauthor = {Mingo, Janire and Erramuzpe, Asier and Luna, Sandra and Aurtenetxe, Olaia and Amo, Laura and Diez, Ibai and Schepens, Jan T. G. and Hendriks, Wiljan J. A. J. and Cortés, Jesús M. and Pulido, Rafael},\n\teditor = {Gill, Andrew C.},\n\tmonth = aug,\n\tyear = {2016},\n\tpages = {e0160972},\n}\n\n\n\n\n\n\n\n

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\n \n\n \n \n \n \n \n \n Vitronectin and dermcidin serum levels predict the metastatic progression of \\textlessspan style=\"font-variant:small-caps;\"\\textgreaterAJCC I–II\\textless/span\\textgreater early‐stage melanoma.\n \n \n \n \n\n\n \n Ortega‐Martínez, I.; Gardeazabal, J.; Erramuzpe, A.; Sanchez‐Diez, A.; Cortés, J.; García‐Vázquez, M. D.; Pérez‐Yarza, G.; Izu, R.; Luís Díaz‐Ramón, J.; De La Fuente, I. M.; Asumendi, A.; and Boyano, M. D.\n\n\n \n\n\n\n International Journal of Cancer, 139(7): 1598–1607. October 2016.\n \n\n\n\n
\n\n\n\n \n \n $\"Vitronectin$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{ortegamartinez_vitronectin_2016,\n\ttitle = {Vitronectin and dermcidin serum levels predict the metastatic progression of {\\textless}span style="font-variant:small-caps;"{\\textgreater}{AJCC} {I}–{II}{\\textless}/span{\\textgreater} early‐stage melanoma},\n\tvolume = {139},\n\tcopyright = {http://creativecommons.org/licenses/by/4.0/},\n\tissn = {0020-7136, 1097-0215},\n\tshorttitle = {Vitronectin and dermcidin serum levels predict the metastatic progression of {\\textless}span style="font-variant},\n\turl = {https://onlinelibrary.wiley.com/doi/10.1002/ijc.30202},\n\tdoi = {10.1002/ijc.30202},\n\tabstract = {Like many cancers, an early diagnosis of melanoma is fundamental to ensure a good prognosis, although an important proportion of stage I–II patients may still develop metastasis during follow‐up. The aim of this work was to discover serum biomarkers in patients diagnosed with primary melanoma that identify those at a high risk of developing metastasis during the follow‐up period. Proteomic and mass spectrophotometry analysis was performed on serum obtained from patients who developed metastasis during the first years after surgery for primary tumors and compared with that from patients who remained disease‐free for more than 10 years after surgery. Five proteins were selected for validation as prognostic factors in 348 melanoma patients and 100 controls by ELISA: serum amyloid A and clusterin; immune system proteins; the cell adhesion molecules plakoglobin and vitronectin and the antimicrobial protein dermcidin. Compared to healthy controls, melanoma patients have high serum levels of these proteins at the moment of melanoma diagnosis, although the specific values were not related to the histopathological stage of the tumors. However, an analysis based on classification together with multivariate statistics showed that tumor stage, vitronectin and dermcidin levels were associated with the metastatic progression of patients with early‐stage melanoma. Although melanoma patients have increased serum dermcidin levels, the REPTree classifier showed that levels of dermcidin {\\textless}2.98 μg/ml predict metastasis in AJCC stage II patients. These data suggest that vitronectin and dermcidin are potent biomarkers of prognosis, which may help to improve the personalized medical care of melanoma patients and their survival.\n          , \n            \n              What's new?\n            \n            The discovery of serum biomarkers capable of predicting metastatic risk during post‐operative follow‐up in early‐stage primary melanoma patients could significantly benefit patient prognosis and survival. The present study identifies two promising biomarker candidates: vitronectin and dermcidin. Analysis and comparison of serum proteins in melanoma patients who either remained disease‐free or developed metastases in the years after surgery to remove primary tumors revealed a strong association between metastatic progression of early‐stage melanomas (AJCC stage III) and vitronectin and dermcidin serum levels. Further study of these proteins could open up new opportunities in the effort to improve long‐term survival among melanoma patients.},\n\tlanguage = {en},\n\tnumber = {7},\n\turldate = {2024-04-15},\n\tjournal = {International Journal of Cancer},\n\tauthor = {Ortega‐Martínez, Idoia and Gardeazabal, Jesús and Erramuzpe, Asier and Sanchez‐Diez, Ana and Cortés, Jesús and García‐Vázquez, María D. and Pérez‐Yarza, Gorka and Izu, Rosa and Luís Díaz‐Ramón, Jose and De La Fuente, Ildefonso M. and Asumendi, Aintzane and Boyano, María D.},\n\tmonth = oct,\n\tyear = {2016},\n\tpages = {1598--1607},\n}\n\n\n\n

\n

\n\n\n

\n Like many cancers, an early diagnosis of melanoma is fundamental to ensure a good prognosis, although an important proportion of stage I–II patients may still develop metastasis during follow‐up. The aim of this work was to discover serum biomarkers in patients diagnosed with primary melanoma that identify those at a high risk of developing metastasis during the follow‐up period. Proteomic and mass spectrophotometry analysis was performed on serum obtained from patients who developed metastasis during the first years after surgery for primary tumors and compared with that from patients who remained disease‐free for more than 10 years after surgery. Five proteins were selected for validation as prognostic factors in 348 melanoma patients and 100 controls by ELISA: serum amyloid A and clusterin; immune system proteins; the cell adhesion molecules plakoglobin and vitronectin and the antimicrobial protein dermcidin. Compared to healthy controls, melanoma patients have high serum levels of these proteins at the moment of melanoma diagnosis, although the specific values were not related to the histopathological stage of the tumors. However, an analysis based on classification together with multivariate statistics showed that tumor stage, vitronectin and dermcidin levels were associated with the metastatic progression of patients with early‐stage melanoma. Although melanoma patients have increased serum dermcidin levels, the REPTree classifier showed that levels of dermcidin \\textless2.98 μg/ml predict metastasis in AJCC stage II patients. These data suggest that vitronectin and dermcidin are potent biomarkers of prognosis, which may help to improve the personalized medical care of melanoma patients and their survival. , What's new? The discovery of serum biomarkers capable of predicting metastatic risk during post‐operative follow‐up in early‐stage primary melanoma patients could significantly benefit patient prognosis and survival. The present study identifies two promising biomarker candidates: vitronectin and dermcidin. Analysis and comparison of serum proteins in melanoma patients who either remained disease‐free or developed metastases in the years after surgery to remove primary tumors revealed a strong association between metastatic progression of early‐stage melanomas (AJCC stage III) and vitronectin and dermcidin serum levels. Further study of these proteins could open up new opportunities in the effort to improve long‐term survival among melanoma patients.\n

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\n \n\n \n \n \n \n \n \n Time-coded neurotransmitter release at excitatory and inhibitory synapses.\n \n \n \n \n\n\n \n Rodrigues, S.; Desroches, M.; Krupa, M.; Cortes, J. M.; Sejnowski, T. J.; and Ali, A. B.\n\n\n \n\n\n\n Proceedings of the National Academy of Sciences, 113(8). February 2016.\n \n\n\n\n
\n\n\n\n \n \n $\"Time-coded$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{rodrigues_time-coded_2016,\n\ttitle = {Time-coded neurotransmitter release at excitatory and inhibitory synapses},\n\tvolume = {113},\n\tissn = {0027-8424, 1091-6490},\n\turl = {https://pnas.org/doi/full/10.1073/pnas.1525591113},\n\tdoi = {10.1073/pnas.1525591113},\n\tabstract = {Significance\n            Neurotransmitter exocytosis and short-term synaptic plasticity (STSP) regulate large-scale brain electrical activity. This study is the first, to our knowledge, proposing a multiple-time-scale model that bridges between the microscopic and mesoscopic scales. It is parsimonious, yet with enough descriptive power to express, on the one hand, the interactions between the SNARE and Sec1/Munc18 (SM) protein complexes mediating all forms of neurotransmitter release and STSP and, on the other hand, the electrical activity required for neuronal communication. A key finding is the discovery of a mathematical structure, termed activity-induced transcritical canard, which quantifies and explains delayed and irregular exocytosis. This structure also provides a previously unidentified way to understand delayed and irregular processes sensitive to initial conditions across various biology processes.\n          , \n            Communication between neurons at chemical synapses is regulated by hundreds of different proteins that control the release of neurotransmitter that is packaged in vesicles, transported to an active zone, and released when an input spike occurs. Neurotransmitter can also be released asynchronously, that is, after a delay following the spike, or spontaneously in the absence of a stimulus. The mechanisms underlying asynchronous and spontaneous neurotransmitter release remain elusive. Here, we describe a model of the exocytotic cycle of vesicles at excitatory and inhibitory synapses that accounts for all modes of vesicle release as well as short-term synaptic plasticity (STSP). For asynchronous release, the model predicts a delayed inertial protein unbinding associated with the SNARE complex assembly immediately after vesicle priming. Experiments are proposed to test the model’s molecular predictions for differential exocytosis. The simplicity of the model will also facilitate large-scale simulations of neural circuits.},\n\tlanguage = {en},\n\tnumber = {8},\n\turldate = {2024-04-15},\n\tjournal = {Proceedings of the National Academy of Sciences},\n\tauthor = {Rodrigues, Serafim and Desroches, Mathieu and Krupa, Martin and Cortes, Jesus M. and Sejnowski, Terrence J. and Ali, Afia B.},\n\tmonth = feb,\n\tyear = {2016},\n}\n\n\n\n\n\n\n\n

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\n \n\n \n \n \n \n \n \n Snail heterogeneity in clear cell renal cell carcinoma.\n \n \n \n \n\n\n \n Zaldumbide, L.; Erramuzpe, A.; Guarch, R.; Pulido, R.; Cortés, J. M.; and López, J. I.\n\n\n \n\n\n\n BMC Cancer, 16(1): 194. December 2016.\n \n\n\n\n
\n\n\n\n \n \n $\"Snail$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{zaldumbide_snail_2016,\n\ttitle = {Snail heterogeneity in clear cell renal cell carcinoma},\n\tvolume = {16},\n\tissn = {1471-2407},\n\turl = {http://www.biomedcentral.com/1471-2407/16/194},\n\tdoi = {10.1186/s12885-016-2237-x},\n\tlanguage = {en},\n\tnumber = {1},\n\turldate = {2024-04-15},\n\tjournal = {BMC Cancer},\n\tauthor = {Zaldumbide, Laura and Erramuzpe, Asier and Guarch, Rosa and Pulido, Rafael and Cortés, Jesús M. and López, José I.},\n\tmonth = dec,\n\tyear = {2016},\n\tpages = {194},\n}\n\n\n\n\n\n\n\n

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\n \n\n \n \n \n \n \n \n Synergetic and Redundant Information Flow Detected by Unnormalized Granger Causality: Application to Resting State fMRI.\n \n \n \n \n\n\n \n \n\n\n \n\n\n\n IEEE Transactions on Biomedical Engineering, 63(12): 2518–2524. December 2016.\n \n\n\n\n
\n\n\n\n \n \n $\"Synergetic$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{noauthor_synergetic_2016,\n\ttitle = {Synergetic and {Redundant} {Information} {Flow} {Detected} by {Unnormalized} {Granger} {Causality}: {Application} to {Resting} {State} {fMRI}},\n\tvolume = {63},\n\tcopyright = {https://ieeexplore.ieee.org/Xplorehelp/downloads/license-information/IEEE.html},\n\tissn = {0018-9294, 1558-2531},\n\tshorttitle = {Synergetic and {Redundant} {Information} {Flow} {Detected} by {Unnormalized} {Granger} {Causality}},\n\turl = {https://ieeexplore.ieee.org/document/7462237/},\n\tdoi = {10.1109/TBME.2016.2559578},\n\tnumber = {12},\n\turldate = {2024-04-15},\n\tjournal = {IEEE Transactions on Biomedical Engineering},\n\tmonth = dec,\n\tyear = {2016},\n\tpages = {2518--2524},\n}\n\n\n\n\n\n\n\n

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\n \n 2015\n \n \n (7)\n \n \n

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\n \n\n \n \n \n \n \n \n Longitudinal variations of brain functional connectivity: A case report study based on a mouse model of epilepsy.\n \n \n \n \n\n\n \n Erramuzpe, A.; Encinas, J. M.; Sierra, A.; Maletic-Savatic, M.; Brewster, A.; Anderson, A. E.; Stramaglia, S.; and Cortes, J. M.\n\n\n \n\n\n\n F1000Research, 4: 144. July 2015.\n \n\n\n\n
\n\n\n\n \n \n $\"Longitudinal$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{erramuzpe_longitudinal_2015,\n\ttitle = {Longitudinal variations of brain functional connectivity: {A} case report study based on a mouse model of epilepsy},\n\tvolume = {4},\n\tissn = {2046-1402},\n\tshorttitle = {Longitudinal variations of brain functional connectivity},\n\turl = {https://f1000research.com/articles/4-144/v2},\n\tdoi = {10.12688/f1000research.6570.2},\n\tabstract = {Brain Functional Connectivity (FC) quantifies statistical dependencies between areas of the brain. FC has been widely used to address altered function of brain circuits in control conditions compared to different pathological states, including epilepsy, a major neurological disorder. However, FC also has the as yet unexplored potential to help us understand the pathological transformation of the brain circuitry. Our hypothesis is that FC can differentiate global brain interactions across a time-scale of days. To this end, we present a case report study based on a mouse model for epilepsy and analyze longitudinal intracranial electroencephalography data of epilepsy to calculate FC changes from the initial insult (status epilepticus) and over the latent period, when epileptogenic networks emerge, and at chronic epilepsy, when unprovoked seizures occur as spontaneous events. We found that the overall network FC at low frequency bands decreased immediately after status epilepticus was provoked, and increased monotonously later on during the latent period. Overall, our results demonstrate the capacity of FC to address longitudinal variations of brain connectivity across the establishment of pathological states.},\n\tlanguage = {en},\n\turldate = {2024-04-15},\n\tjournal = {F1000Research},\n\tauthor = {Erramuzpe, A. and Encinas, J. M. and Sierra, A. and Maletic-Savatic, M. and Brewster, A.L. and Anderson, Anne E. and Stramaglia, S. and Cortes, Jesus M.},\n\tmonth = jul,\n\tyear = {2015},\n\tpages = {144},\n}\n\n\n\n\n\n\n\n\n\n\n\n

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\n \n\n \n \n \n \n \n \n Lagged and instantaneous dynamical influences related to brain structural connectivity.\n \n \n \n \n\n\n \n Alonso-Montes, C.; Diez, I.; Remaki, L.; Escudero, I.; Mateos, B.; Rosseel, Y.; Marinazzo, D.; Stramaglia, S.; and Cortes, J. M.\n\n\n \n\n\n\n Frontiers in Psychology, 6. July 2015.\n \n\n\n\n
\n\n\n\n \n \n $\"Lagged$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{alonso-montes_lagged_2015,\n\ttitle = {Lagged and instantaneous dynamical influences related to brain structural connectivity},\n\tvolume = {6},\n\tissn = {1664-1078},\n\turl = {http://journal.frontiersin.org/Article/10.3389/fpsyg.2015.01024/abstract},\n\tdoi = {10.3389/fpsyg.2015.01024},\n\turldate = {2024-04-15},\n\tjournal = {Frontiers in Psychology},\n\tauthor = {Alonso-Montes, Carmen and Diez, Ibai and Remaki, Lakhdar and Escudero, Iñaki and Mateos, Beatriz and Rosseel, Yves and Marinazzo, Daniele and Stramaglia, Sebastiano and Cortes, Jesus M.},\n\tmonth = jul,\n\tyear = {2015},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Information Flow Between Resting-State Networks.\n \n \n \n \n\n\n \n Diez, I.; Erramuzpe, A.; Escudero, I.; Mateos, B.; Cabrera, A.; Marinazzo, D.; Sanz-Arigita, E. J.; Stramaglia, S.; Cortes Diaz, J. M.; and for the Alzheimer's Disease Neuroimaging Initiative\n\n\n \n\n\n\n Brain Connectivity, 5(9): 554–564. November 2015.\n \n\n\n\n
\n\n\n\n \n \n $\"Information$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{diez_information_2015,\n\ttitle = {Information {Flow} {Between} {Resting}-{State} {Networks}},\n\tvolume = {5},\n\tissn = {2158-0014, 2158-0022},\n\turl = {http://www.liebertpub.com/doi/10.1089/brain.2014.0337},\n\tdoi = {10.1089/brain.2014.0337},\n\tlanguage = {en},\n\tnumber = {9},\n\turldate = {2024-04-15},\n\tjournal = {Brain Connectivity},\n\tauthor = {Diez, Ibai and Erramuzpe, Asier and Escudero, Iñaki and Mateos, Beatriz and Cabrera, Alberto and Marinazzo, Daniele and Sanz-Arigita, Ernesto J. and Stramaglia, Sebastiano and Cortes Diaz, Jesus M. and {for the Alzheimer's Disease Neuroimaging Initiative}},\n\tmonth = nov,\n\tyear = {2015},\n\tpages = {554--564},\n}\n\n\n\n\n\n\n\n

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\n \n\n \n \n \n \n \n \n Identification of redundant and synergetic circuits in triplets of electrophysiological data.\n \n \n \n \n\n\n \n Erramuzpe, A.; Ortega, G. J; Pastor, J.; Sola, R. G D.; Marinazzo, D.; Stramaglia, S.; and Cortes, J. M\n\n\n \n\n\n\n Journal of Neural Engineering, 12(6): 066007. December 2015.\n \n\n\n\n
\n\n\n\n \n \n $\"Identification$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{erramuzpe_identification_2015,\n\ttitle = {Identification of redundant and synergetic circuits in triplets of electrophysiological data},\n\tvolume = {12},\n\tissn = {1741-2560, 1741-2552},\n\turl = {https://iopscience.iop.org/article/10.1088/1741-2560/12/6/066007},\n\tdoi = {10.1088/1741-2560/12/6/066007},\n\tnumber = {6},\n\turldate = {2024-04-15},\n\tjournal = {Journal of Neural Engineering},\n\tauthor = {Erramuzpe, Asier and Ortega, Guillermo J and Pastor, Jesus and Sola, Rafael G De and Marinazzo, Daniele and Stramaglia, Sebastiano and Cortes, Jesus M},\n\tmonth = dec,\n\tyear = {2015},\n\tpages = {066007},\n}\n\n\n\n\n\n\n\n

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\n \n\n \n \n \n \n \n \n A novel brain partition highlights the modular skeleton shared by structure and function.\n \n \n \n \n\n\n \n Diez, I.; Bonifazi, P.; Escudero, I.; Mateos, B.; Muñoz, M. A.; Stramaglia, S.; and Cortes, J. M.\n\n\n \n\n\n\n Scientific Reports, 5(1): 10532. June 2015.\n \n\n\n\n
\n\n\n\n \n \n $\"A$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{diez_novel_2015,\n\ttitle = {A novel brain partition highlights the modular skeleton shared by structure and function},\n\tvolume = {5},\n\tissn = {2045-2322},\n\turl = {https://www.nature.com/articles/srep10532},\n\tdoi = {10.1038/srep10532},\n\tabstract = {Abstract\n            Elucidating the intricate relationship between brain structure and function, both in healthy and pathological conditions, is a key challenge for modern neuroscience. Recent progress in neuroimaging has helped advance our understanding of this important issue, with diffusion images providing information about structural connectivity (SC) and functional magnetic resonance imaging shedding light on resting state functional connectivity (rsFC). Here, we adopt a systems approach, relying on modular hierarchical clustering, to study together SC and rsFC datasets gathered independently from healthy human subjects. Our novel approach allows us to find a common skeleton shared by structure and function from which a new, optimal, brain partition can be extracted. We describe the emerging common structure-function modules (SFMs) in detail and compare them with commonly employed anatomical or functional parcellations. Our results underline the strong correspondence between brain structure and resting-state dynamics as well as the emerging coherent organization of the human brain.},\n\tlanguage = {en},\n\tnumber = {1},\n\turldate = {2024-04-15},\n\tjournal = {Scientific Reports},\n\tauthor = {Diez, Ibai and Bonifazi, Paolo and Escudero, Iñaki and Mateos, Beatriz and Muñoz, Miguel A. and Stramaglia, Sebastiano and Cortes, Jesus M.},\n\tmonth = jun,\n\tyear = {2015},\n\tpages = {10532},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Synergy, redundancy and unnormalized Granger causality.\n \n \n \n \n\n\n \n Stramaglia, S.; Angelini, L.; Cortes, J. M.; and Marinazzo, D.\n\n\n \n\n\n\n In 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), pages 4037–4040, Milan, August 2015. IEEE\n \n\n\n\n
\n\n\n\n \n \n $\"Synergy,$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@inproceedings{stramaglia_synergy_2015,\n\taddress = {Milan},\n\ttitle = {Synergy, redundancy and unnormalized {Granger} causality},\n\tisbn = {978-1-4244-9271-8},\n\turl = {http://ieeexplore.ieee.org/document/7319280/},\n\tdoi = {10.1109/EMBC.2015.7319280},\n\turldate = {2024-04-15},\n\tbooktitle = {2015 37th {Annual} {International} {Conference} of the {IEEE} {Engineering} in {Medicine} and {Biology} {Society} ({EMBC})},\n\tpublisher = {IEEE},\n\tauthor = {Stramaglia, S. and Angelini, L. and Cortes, J. M. and Marinazzo, D.},\n\tmonth = aug,\n\tyear = {2015},\n\tpages = {4037--4040},\n}\n\n\n\n\n\n\n\n

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\n \n\n \n \n \n \n \n \n Large (\\textgreater3.8 cm) clear cell renal cell carcinomas are morphologically and immunohistochemically heterogeneous.\n \n \n \n \n\n\n \n Zaldumbide, L.; Erramuzpe, A.; Guarch, R.; Cortés, J. M.; and López, J. I.\n\n\n \n\n\n\n Virchows Archiv, 466(1): 61–66. January 2015.\n \n\n\n\n
\n\n\n\n \n \n $\"Large$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{zaldumbide_large_2015,\n\ttitle = {Large ({\\textgreater}3.8 cm) clear cell renal cell carcinomas are morphologically and immunohistochemically heterogeneous},\n\tvolume = {466},\n\tissn = {0945-6317, 1432-2307},\n\turl = {http://link.springer.com/10.1007/s00428-014-1673-8},\n\tdoi = {10.1007/s00428-014-1673-8},\n\tlanguage = {en},\n\tnumber = {1},\n\turldate = {2024-04-15},\n\tjournal = {Virchows Archiv},\n\tauthor = {Zaldumbide, Laura and Erramuzpe, Asier and Guarch, Rosa and Cortés, Jesús M. and López, José I.},\n\tmonth = jan,\n\tyear = {2015},\n\tpages = {61--66},\n}\n\n\n\n\n\n\n\n

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\n \n 2014\n \n \n (3)\n \n \n

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\n \n\n \n \n \n \n \n \n On the Dynamics of the Adenylate Energy System: Homeorhesis vs Homeostasis.\n \n \n \n \n\n\n \n De La Fuente, I. M.; Cortés, J. M.; Valero, E.; Desroches, M.; Rodrigues, S.; Malaina, I.; and Martínez, L.\n\n\n \n\n\n\n PLoS ONE, 9(10): e108676. October 2014.\n \n\n\n\n
\n\n\n\n \n \n $\"On$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{de_la_fuente_dynamics_2014,\n\ttitle = {On the {Dynamics} of the {Adenylate} {Energy} {System}: {Homeorhesis} vs {Homeostasis}},\n\tvolume = {9},\n\tissn = {1932-6203},\n\tshorttitle = {On the {Dynamics} of the {Adenylate} {Energy} {System}},\n\turl = {https://dx.plos.org/10.1371/journal.pone.0108676},\n\tdoi = {10.1371/journal.pone.0108676},\n\tlanguage = {en},\n\tnumber = {10},\n\turldate = {2024-04-15},\n\tjournal = {PLoS ONE},\n\tauthor = {De La Fuente, Ildefonso M. and Cortés, Jesús M. and Valero, Edelmira and Desroches, Mathieu and Rodrigues, Serafim and Malaina, Iker and Martínez, Luis},\n\teditor = {Virolle, Marie-Joelle},\n\tmonth = oct,\n\tyear = {2014},\n\tpages = {e108676},\n}\n\n\n\n\n\n\n\n

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\n \n\n \n \n \n \n \n \n Editorial for the research topic: information-based methods for neuroimaging: analyzing structure, function and dynamics.\n \n \n \n \n\n\n \n Cortes, J. M.; Marinazzo, D.; and MuÃ±oz, M. A.\n\n\n \n\n\n\n Frontiers in Neuroinformatics, 8. December 2014.\n \n\n\n\n
\n\n\n\n \n \n $\"Editorial$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{cortes_editorial_2014,\n\ttitle = {Editorial for the research topic: information-based methods for neuroimaging: analyzing structure, function and dynamics},\n\tvolume = {8},\n\tissn = {1662-5196},\n\tshorttitle = {Editorial for the research topic},\n\turl = {http://journal.frontiersin.org/article/10.3389/fninf.2014.00086/abstract},\n\tdoi = {10.3389/fninf.2014.00086},\n\turldate = {2024-04-15},\n\tjournal = {Frontiers in Neuroinformatics},\n\tauthor = {Cortes, Jesus M. and Marinazzo, Daniele and MuÃ±oz, Miguel A.},\n\tmonth = dec,\n\tyear = {2014},\n}\n\n\n\n

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\n \n\n \n \n \n \n \n \n Information Transfer and Criticality in the Ising Model on the Human Connectome.\n \n \n \n \n\n\n \n Marinazzo, D.; Pellicoro, M.; Wu, G.; Angelini, L.; Cortés, J. M.; and Stramaglia, S.\n\n\n \n\n\n\n PLoS ONE, 9(4): e93616. April 2014.\n \n\n\n\n
\n\n\n\n \n \n $\"Information$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{marinazzo_information_2014,\n\ttitle = {Information {Transfer} and {Criticality} in the {Ising} {Model} on the {Human} {Connectome}},\n\tvolume = {9},\n\tissn = {1932-6203},\n\turl = {https://dx.plos.org/10.1371/journal.pone.0093616},\n\tdoi = {10.1371/journal.pone.0093616},\n\tlanguage = {en},\n\tnumber = {4},\n\turldate = {2024-04-15},\n\tjournal = {PLoS ONE},\n\tauthor = {Marinazzo, Daniele and Pellicoro, Mario and Wu, Guorong and Angelini, Leonardo and Cortés, Jesús M. and Stramaglia, Sebastiano},\n\teditor = {Lambiotte, Renaud},\n\tmonth = apr,\n\tyear = {2014},\n\tpages = {e93616},\n}\n\n\n\n\n\n\n\n

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\n \n 2013\n \n \n (3)\n \n \n

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\n \n\n \n \n \n \n \n \n Short-term synaptic plasticity in the deterministic Tsodyks–Markram model leads to unpredictable network dynamics.\n \n \n \n \n\n\n \n Cortes, J. M.; Desroches, M.; Rodrigues, S.; Veltz, R.; Muñoz, M. A.; and Sejnowski, T. J.\n\n\n \n\n\n\n Proceedings of the National Academy of Sciences, 110(41): 16610–16615. October 2013.\n \n\n\n\n
\n\n\n\n \n \n $\"Short-term$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n \n \n abstract \n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{cortes_short-term_2013,\n\ttitle = {Short-term synaptic plasticity in the deterministic {Tsodyks}–{Markram} model leads to unpredictable network dynamics},\n\tvolume = {110},\n\tissn = {0027-8424, 1091-6490},\n\turl = {https://pnas.org/doi/full/10.1073/pnas.1316071110},\n\tdoi = {10.1073/pnas.1316071110},\n\tabstract = {Significance\n            Short-term synaptic plasticity contributes to the balance and regulation of brain networks from milliseconds to several minutes. In this paper we report the existence of a route to chaos in the Tsodyks and Markram model of short-term synaptic plasticity. The chaotic region corresponds to what in mathematics is called Shilnikov chaos, an unstable manifold that strongly modifies the shape of trajectories and induces highly irregular transient dynamics, even in the absence of noise. The interplay between the Shilnikov chaos and stochastic effects may give rise to some of the complex dynamics observed in neural systems such as transitions between up and down states.\n          , \n            Short-term synaptic plasticity strongly affects the neural dynamics of cortical networks. The Tsodyks and Markram (TM) model for short-term synaptic plasticity accurately accounts for a wide range of physiological responses at different types of cortical synapses. Here, we report a route to chaotic behavior via a Shilnikov homoclinic bifurcation that dynamically organizes some of the responses in the TM model. In particular, the presence of such a homoclinic bifurcation strongly affects the shape of the trajectories in the phase space and induces highly irregular transient dynamics; indeed, in the vicinity of the Shilnikov homoclinic bifurcation, the number of population spikes and their precise timing are unpredictable and highly sensitive to the initial conditions. Such an irregular deterministic dynamics has its counterpart in stochastic/network versions of the TM model: The existence of the Shilnikov homoclinic bifurcation generates complex and irregular spiking patterns and—acting as a sort of springboard—facilitates transitions between the down-state and unstable periodic orbits. The interplay between the (deterministic) homoclinic bifurcation and stochastic effects may give rise to some of the complex dynamics observed in neural systems.},\n\tlanguage = {en},\n\tnumber = {41},\n\turldate = {2024-04-15},\n\tjournal = {Proceedings of the National Academy of Sciences},\n\tauthor = {Cortes, Jesus M. and Desroches, Mathieu and Rodrigues, Serafim and Veltz, Romain and Muñoz, Miguel A. and Sejnowski, Terrence J.},\n\tmonth = oct,\n\tyear = {2013},\n\tpages = {16610--16615},\n}\n\n\n\n\n\n\n\n

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\n \n\n \n \n \n \n \n \n Attractor Metabolic Networks.\n \n \n \n \n\n\n \n De La Fuente, I. M.; Cortes, J. M.; Pelta, D. A.; and Veguillas, J.\n\n\n \n\n\n\n PLoS ONE, 8(3): e58284. March 2013.\n \n\n\n\n
\n\n\n\n \n \n $\"Attractor$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{de_la_fuente_attractor_2013,\n\ttitle = {Attractor {Metabolic} {Networks}},\n\tvolume = {8},\n\tissn = {1932-6203},\n\turl = {https://dx.plos.org/10.1371/journal.pone.0058284},\n\tdoi = {10.1371/journal.pone.0058284},\n\tlanguage = {en},\n\tnumber = {3},\n\turldate = {2024-04-15},\n\tjournal = {PLoS ONE},\n\tauthor = {De La Fuente, Ildefonso M. and Cortes, Jesus M. and Pelta, David A. and Veguillas, Juan},\n\teditor = {Torres, Nestor V.},\n\tmonth = mar,\n\tyear = {2013},\n\tpages = {e58284},\n}\n\n\n\n\n\n\n\n

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\n \n\n \n \n \n \n \n \n Disruption of transfer entropy and inter-hemispheric brain functional connectivity in patients with disorder of consciousness.\n \n \n \n \n\n\n \n Mäki-Marttunen, V.; Diez, I.; Cortes, J. M.; Chialvo, D. R.; and Villarreal, M.\n\n\n \n\n\n\n Frontiers in Neuroinformatics, 7. 2013.\n \n\n\n\n
\n\n\n\n \n \n $\"Disruption$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{maki-marttunen_disruption_2013,\n\ttitle = {Disruption of transfer entropy and inter-hemispheric brain functional connectivity in patients with disorder of consciousness},\n\tvolume = {7},\n\tissn = {1662-5196},\n\turl = {http://journal.frontiersin.org/article/10.3389/fninf.2013.00024/abstract},\n\tdoi = {10.3389/fninf.2013.00024},\n\turldate = {2024-04-15},\n\tjournal = {Frontiers in Neuroinformatics},\n\tauthor = {Mäki-Marttunen, Verónica and Diez, Ibai and Cortes, Jesus M. and Chialvo, Dante R. and Villarreal, Mirta},\n\tyear = {2013},\n}\n\n\n\n

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\n \n 2012\n \n \n (1)\n \n \n

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\n \n\n \n \n \n \n \n \n Stochastic Amplification of Fluctuations in Cortical Up-States.\n \n \n \n \n\n\n \n Hidalgo, J.; Seoane, L. F.; Cortés, J. M.; and Muñoz, M. A.\n\n\n \n\n\n\n PLoS ONE, 7(8): e40710. August 2012.\n \n\n\n\n
\n\n\n\n \n \n $\"Stochastic$ Paper\n \n \n\n \n \n doi\n \n \n\n \n link\n \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n \n \n \n\n\n\n

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@article{hidalgo_stochastic_2012,\n\ttitle = {Stochastic {Amplification} of {Fluctuations} in {Cortical} {Up}-{States}},\n\tvolume = {7},\n\tissn = {1932-6203},\n\turl = {https://dx.plos.org/10.1371/journal.pone.0040710},\n\tdoi = {10.1371/journal.pone.0040710},\n\tlanguage = {en},\n\tnumber = {8},\n\turldate = {2024-04-15},\n\tjournal = {PLoS ONE},\n\tauthor = {Hidalgo, Jorge and Seoane, Luís F. and Cortés, Jesús M. and Muñoz, Miguel A.},\n\teditor = {Chialvo, Dante R.},\n\tmonth = aug,\n\tyear = {2012},\n\tpages = {e40710},\n}\n\n\n\n\n\n\n\n\n\n\n\n

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